Storage efficiency driven migration

ABSTRACT

Storage efficiency driven migration includes: determining a level of similarity between first data stored on a first storage system and second data stored on a second storage system; determining, in dependence upon the level of similarity, that an expected amount of storage space reduction from migrating similar data exceeds a threshold level; and responsive to determining that the expected amount of storage space reduction exceeds the threshold level, initiating a migration of one or more portions of the first data from the first storage system to the second storage system.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1A illustrates a first example system for data storage inaccordance with some implementations.

FIG. 1B illustrates a second example system for data storage inaccordance with some implementations.

FIG. 1C illustrates a third example system for data storage inaccordance with some implementations.

FIG. 1D illustrates a fourth example system for data storage inaccordance with some implementations.

FIG. 2A is a perspective view of a storage cluster with multiple storagenodes and internal storage coupled to each storage node to providenetwork attached storage, in accordance with some embodiments.

FIG. 2B is a block diagram showing an interconnect switch couplingmultiple storage nodes in accordance with some embodiments.

FIG. 2C is a multiple level block diagram, showing contents of a storagenode and contents of one of the non-volatile solid state storage unitsin accordance with some embodiments.

FIG. 2D shows a storage server environment, which uses embodiments ofthe storage nodes and storage units of some previous figures inaccordance with some embodiments.

FIG. 2E is a blade hardware block diagram, showing a control plane,compute and storage planes, and authorities interacting with underlyingphysical resources, in accordance with some embodiments.

FIG. 2F depicts elasticity software layers in blades of a storagecluster, in accordance with some embodiments.

FIG. 2G depicts authorities and storage resources in blades of a storagecluster, in accordance with some embodiments.

FIG. 3A sets forth a diagram of a storage system that is coupled fordata communications with a cloud services provider in accordance withsome embodiments of the present disclosure.

FIG. 3B sets forth a diagram of a storage system in accordance with someembodiments of the present disclosure.

FIG. 3C sets forth a diagram of multiple storage systems in accordancewith some embodiments of the present disclosure.

FIG. 3D sets forth a diagram of multiple storage systems in accordancewith some embodiments of the present disclosure.

FIG. 3E sets forth a flow chart illustrating an example method forsynchronous replication according to some embodiments of the presentdisclosure.

FIG. 3F sets forth a diagram of multiple storage systems in accordancewith some embodiments of the present disclosure.

FIG. 4 sets forth a flow chart illustrating an example method forstorage efficiency driven migration according to some embodiments of thepresent disclosure.

FIG. 5 sets forth a flow chart illustrating an example method forstorage efficiency driven migration according to some embodiments of thepresent disclosure.

FIG. 6 sets forth a flow chart illustrating an example method forstorage efficiency driven migration according to some embodiments of thepresent disclosure.

FIG. 7 sets forth a flow chart illustrating an example method forstorage efficiency driven migration according to some embodiments of thepresent disclosure.

FIG. 8 sets forth a flow chart illustrating an example method forstorage efficiency driven migration according to some embodiments of thepresent disclosure.

FIG. 9 sets forth a flow chart illustrating an example method forstorage efficiency driven migration according to some embodiments of thepresent disclosure.

FIG. 10 sets forth a flow chart illustrating an example method forstorage efficiency driven migration according to some embodiments of thepresent disclosure.

DESCRIPTION OF EMBODIMENTS

Example methods, apparatus, and products for storage efficiency drivenmigration in accordance with embodiments of the present disclosure aredescribed with reference to the accompanying drawings, beginning withFIG. 1A. FIG. 1A illustrates an example system for data storage, inaccordance with some implementations. System 100 (also referred to as“storage system” herein) includes numerous elements for purposes ofillustration rather than limitation. It may be noted that system 100 mayinclude the same, more, or fewer elements configured in the same ordifferent manner in other implementations.

System 100 includes a number of computing devices 164A-B. Computingdevices (also referred to as “client devices” herein) may be embodied,for example, a server in a data center, a workstation, a personalcomputer, a notebook, or the like. Computing devices 164A-B may becoupled for data communications to one or more storage arrays 102A-Bthrough a storage area network (‘SAN’) 158 or a local area network(‘LAN’) 160.

The SAN 158 may be implemented with a variety of data communicationsfabrics, devices, and protocols. For example, the fabrics for SAN 158may include Fibre Channel, Ethernet, Infiniband, Serial Attached SmallComputer System Interface (‘SAS’), or the like. Data communicationsprotocols for use with SAN 158 may include Advanced TechnologyAttachment (‘ATA’), Fibre Channel Protocol, Small Computer SystemInterface (‘SCSI’), Internet Small Computer System Interface (‘iSCSI’),HyperSCSI, Non-Volatile Memory Express (‘NVMe’) over Fabrics, or thelike. It may be noted that SAN 158 is provided for illustration, ratherthan limitation. Other data communication couplings may be implementedbetween computing devices 164A-B and storage arrays 102A-B.

The LAN 160 may also be implemented with a variety of fabrics, devices,and protocols. For example, the fabrics for LAN 160 may include Ethernet(802.3), wireless (802.11), or the like. Data communication protocolsfor use in LAN 160 may include Transmission Control Protocol (‘TCP’),User Datagram Protocol (‘UDP’), Internet Protocol (‘IP’), HyperTextTransfer Protocol (‘HTTP’), Wireless Access Protocol (‘WAP’), HandheldDevice Transport Protocol (‘HDTP’), Session Initiation Protocol (‘SIP’),Real Time Protocol (‘RTP’), or the like.

Storage arrays 102A-B may provide persistent data storage for thecomputing devices 164A-B. Storage array 102A may be contained in achassis (not shown), and storage array 102B may be contained in anotherchassis (not shown), in implementations. Storage array 102A and 102B mayinclude one or more storage array controllers 110 (also referred to as“controller” herein). A storage array controller 110 may be embodied asa module of automated computing machinery comprising computer hardware,computer software, or a combination of computer hardware and software.In some implementations, the storage array controllers 110 may beconfigured to carry out various storage tasks. Storage tasks may includewriting data received from the computing devices 164A-B to storage array102A-B, erasing data from storage array 102A-B, retrieving data fromstorage array 102A-B and providing data to computing devices 164A-B,monitoring and reporting of disk utilization and performance, performingredundancy operations, such as Redundant Array of Independent Drives(‘RAID’) or RAID-like data redundancy operations, compressing data,encrypting data, and so forth.

Storage array controller 110 may be implemented in a variety of ways,including as a Field Programmable Gate Array (‘FPGA’), a ProgrammableLogic Chip (‘PLC’), an Application Specific Integrated Circuit (‘ASIC’),System-on-Chip (‘SOC’), or any computing device that includes discretecomponents such as a processing device, central processing unit,computer memory, or various adapters. Storage array controller 110 mayinclude, for example, a data communications adapter configured tosupport communications via the SAN 158 or LAN 160. In someimplementations, storage array controller 110 may be independentlycoupled to the LAN 160. In implementations, storage array controller 110may include an I/O controller or the like that couples the storage arraycontroller 110 for data communications, through a midplane (not shown),to a persistent storage resource 170A-B (also referred to as a “storageresource” herein). The persistent storage resource 170A-B main includeany number of storage drives 171A-F (also referred to as “storagedevices” herein) and any number of non-volatile Random Access Memory(‘NVRAM’) devices (not shown).

In some implementations, the NVRAM devices of a persistent storageresource 170A-B may be configured to receive, from the storage arraycontroller 110, data to be stored in the storage drives 171A-F. In someexamples, the data may originate from computing devices 164A-B. In someexamples, writing data to the NVRAM device may be carried out morequickly than directly writing data to the storage drive 171A-F. Inimplementations, the storage array controller 110 may be configured toutilize the NVRAM devices as a quickly accessible buffer for datadestined to be written to the storage drives 171A-F. Latency for writerequests using NVRAM devices as a buffer may be improved relative to asystem in which a storage array controller 110 writes data directly tothe storage drives 171A-F. In some implementations, the NVRAM devicesmay be implemented with computer memory in the form of high bandwidth,low latency RAM. The NVRAM device is referred to as “non-volatile”because the NVRAM device may receive or include a unique power sourcethat maintains the state of the RAM after main power loss to the NVRAMdevice. Such a power source may be a battery, one or more capacitors, orthe like. In response to a power loss, the NVRAM device may beconfigured to write the contents of the RAM to a persistent storage,such as the storage drives 171A-F.

In implementations, storage drive 171A-F may refer to any deviceconfigured to record data persistently, where “persistently” or“persistent” refers to a device's ability to maintain recorded dataafter loss of power. In some implementations, storage drive 171A-F maycorrespond to non-disk storage media. For example, the storage drive171A-F may be one or more solid-state drives (‘SSDs’), flash memorybased storage, any type of solid-state non-volatile memory, or any othertype of non-mechanical storage device. In other implementations, storagedrive 171A-F may include mechanical or spinning hard disk, such ashard-disk drives (‘HDD’).

In some implementations, the storage array controllers 110 may beconfigured for offloading device management responsibilities fromstorage drive 171A-F in storage array 102A-B. For example, storage arraycontrollers 110 may manage control information that may describe thestate of one or more memory blocks in the storage drives 171A-F. Thecontrol information may indicate, for example, that a particular memoryblock has failed and should no longer be written to, that a particularmemory block contains boot code for a storage array controller 110, thenumber of program-erase (‘P/E’) cycles that have been performed on aparticular memory block, the age of data stored in a particular memoryblock, the type of data that is stored in a particular memory block, andso forth. In some implementations, the control information may be storedwith an associated memory block as metadata. In other implementations,the control information for the storage drives 171A-F may be stored inone or more particular memory blocks of the storage drives 171A-F thatare selected by the storage array controller 110. The selected memoryblocks may be tagged with an identifier indicating that the selectedmemory block contains control information. The identifier may beutilized by the storage array controllers 110 in conjunction withstorage drives 171A-F to quickly identify the memory blocks that containcontrol information. For example, the storage controllers 110 may issuea command to locate memory blocks that contain control information. Itmay be noted that control information may be so large that parts of thecontrol information may be stored in multiple locations, that thecontrol information may be stored in multiple locations for purposes ofredundancy, for example, or that the control information may otherwisebe distributed across multiple memory blocks in the storage drive171A-F.

In implementations, storage array controllers 110 may offload devicemanagement responsibilities from storage drives 171A-F of storage array102A-B by retrieving, from the storage drives 171A-F, controlinformation describing the state of one or more memory blocks in thestorage drives 171A-F. Retrieving the control information from thestorage drives 171A-F may be carried out, for example, by the storagearray controller 110 querying the storage drives 171A-F for the locationof control information for a particular storage drive 171A-F. Thestorage drives 171A-F may be configured to execute instructions thatenable the storage drive 171A-F to identify the location of the controlinformation. The instructions may be executed by a controller (notshown) associated with or otherwise located on the storage drive 171A-Fand may cause the storage drive 171A-F to scan a portion of each memoryblock to identify the memory blocks that store control information forthe storage drives 171A-F. The storage drives 171A-F may respond bysending a response message to the storage array controller 110 thatincludes the location of control information for the storage drive171A-F. Responsive to receiving the response message, storage arraycontrollers 110 may issue a request to read data stored at the addressassociated with the location of control information for the storagedrives 171A-F.

In other implementations, the storage array controllers 110 may furtheroffload device management responsibilities from storage drives 171A-F byperforming, in response to receiving the control information, a storagedrive management operation. A storage drive management operation mayinclude, for example, an operation that is typically performed by thestorage drive 171A-F (e.g., the controller (not shown) associated with aparticular storage drive 171A-F). A storage drive management operationmay include, for example, ensuring that data is not written to failedmemory blocks within the storage drive 171A-F, ensuring that data iswritten to memory blocks within the storage drive 171A-F in such a waythat adequate wear leveling is achieved, and so forth.

In implementations, storage array 102A-B may implement two or morestorage array controllers 110. For example, storage array 102A mayinclude storage array controllers 110A and storage array controllers110B. At a given instance, a single storage array controller 110 (e.g.,storage array controller 110A) of a storage system 100 may be designatedwith primary status (also referred to as “primary controller” herein),and other storage array controllers 110 (e.g., storage array controller110A) may be designated with secondary status (also referred to as“secondary controller” herein). The primary controller may haveparticular rights, such as permission to alter data in persistentstorage resource 170A-B (e.g., writing data to persistent storageresource 170A-B). At least some of the rights of the primary controllermay supersede the rights of the secondary controller. For instance, thesecondary controller may not have permission to alter data in persistentstorage resource 170A-B when the primary controller has the right. Thestatus of storage array controllers 110 may change. For example, storagearray controller 110A may be designated with secondary status, andstorage array controller 110B may be designated with primary status.

In some implementations, a primary controller, such as storage arraycontroller 110A, may serve as the primary controller for one or morestorage arrays 102A-B, and a second controller, such as storage arraycontroller 110B, may serve as the secondary controller for the one ormore storage arrays 102A-B. For example, storage array controller 110Amay be the primary controller for storage array 102A and storage array102B, and storage array controller 110B may be the secondary controllerfor storage array 102A and 102B. In some implementations, storage arraycontrollers 110C and 110D (also referred to as “storage processingmodules”) may neither have primary or secondary status. Storage arraycontrollers 110C and 110D, implemented as storage processing modules,may act as a communication interface between the primary and secondarycontrollers (e.g., storage array controllers 110A and 110B,respectively) and storage array 102B. For example, storage arraycontroller 110A of storage array 102A may send a write request, via SAN158, to storage array 102B. The write request may be received by bothstorage array controllers 110C and 110D of storage array 102B. Storagearray controllers 110C and 110D facilitate the communication, e.g., sendthe write request to the appropriate storage drive 171A-F. It may benoted that in some implementations storage processing modules may beused to increase the number of storage drives controlled by the primaryand secondary controllers.

In implementations, storage array controllers 110 are communicativelycoupled, via a midplane (not shown), to one or more storage drives171A-F and to one or more NVRAM devices (not shown) that are included aspart of a storage array 102A-B. The storage array controllers 110 may becoupled to the midplane via one or more data communication links and themidplane may be coupled to the storage drives 171A-F and the NVRAMdevices via one or more data communications links. The datacommunications links described herein are collectively illustrated bydata communications links 108A-D and may include a Peripheral ComponentInterconnect Express (‘PCIe’) bus, for example.

FIG. 1B illustrates an example system for data storage, in accordancewith some implementations. Storage array controller 101 illustrated inFIG. 1B may similar to the storage array controllers 110 described withrespect to FIG. 1A. In one example, storage array controller 101 may besimilar to storage array controller 110A or storage array controller110B. Storage array controller 101 includes numerous elements forpurposes of illustration rather than limitation. It may be noted thatstorage array controller 101 may include the same, more, or fewerelements configured in the same or different manner in otherimplementations. It may be noted that elements of FIG. 1A may beincluded below to help illustrate features of storage array controller101.

Storage array controller 101 may include one or more processing devices104 and random access memory (‘RAM’) 111. Processing device 104 (orcontroller 101) represents one or more general-purpose processingdevices such as a microprocessor, central processing unit, or the like.More particularly, the processing device 104 (or controller 101) may bea complex instruction set computing (‘CISC’) microprocessor, reducedinstruction set computing (‘RISC’) microprocessor, very long instructionword (‘VLIW’) microprocessor, or a processor implementing otherinstruction sets or processors implementing a combination of instructionsets. The processing device 104 (or controller 101) may also be one ormore special-purpose processing devices such as an application specificintegrated circuit (‘ASIC’), a field programmable gate array (‘FPGA’), adigital signal processor (‘DSP’), network processor, or the like.

The processing device 104 may be connected to the RAM 111 via a datacommunications link 106, which may be embodied as a high speed memorybus such as a Double-Data Rate 4 (‘DDR4’) bus. Stored in RAM 111 is anoperating system 112. In some implementations, instructions 113 arestored in RAM 111. Instructions 113 may include computer programinstructions for performing operations in in a direct-mapped flashstorage system. In one embodiment, a direct-mapped flash storage systemis one that that addresses data blocks within flash drives directly andwithout an address translation performed by the storage controllers ofthe flash drives.

In implementations, storage array controller 101 includes one or morehost bus adapters 103A-C that are coupled to the processing device 104via a data communications link 105A-C. In implementations, host busadapters 103A-C may be computer hardware that connects a host system(e.g., the storage array controller) to other network and storagearrays. In some examples, host bus adapters 103A-C may be a FibreChannel adapter that enables the storage array controller 101 to connectto a SAN, an Ethernet adapter that enables the storage array controller101 to connect to a LAN, or the like. Host bus adapters 103A-C may becoupled to the processing device 104 via a data communications link105A-C such as, for example, a PCIe bus.

In implementations, storage array controller 101 may include a host busadapter 114 that is coupled to an expander 115. The expander 115 may beused to attach a host system to a larger number of storage drives. Theexpander 115 may, for example, be a SAS expander utilized to enable thehost bus adapter 114 to attach to storage drives in an implementationwhere the host bus adapter 114 is embodied as a SAS controller.

In implementations, storage array controller 101 may include a switch116 coupled to the processing device 104 via a data communications link109. The switch 116 may be a computer hardware device that can createmultiple endpoints out of a single endpoint, thereby enabling multipledevices to share a single endpoint. The switch 116 may, for example, bea PCIe switch that is coupled to a PCIe bus (e.g., data communicationslink 109) and presents multiple PCIe connection points to the midplane.

In implementations, storage array controller 101 includes a datacommunications link 107 for coupling the storage array controller 101 toother storage array controllers. In some examples, data communicationslink 107 may be a QuickPath Interconnect (QPI) interconnect.

A traditional storage system that uses traditional flash drives mayimplement a process across the flash drives that are part of thetraditional storage system. For example, a higher level process of thestorage system may initiate and control a process across the flashdrives. However, a flash drive of the traditional storage system mayinclude its own storage controller that also performs the process. Thus,for the traditional storage system, a higher level process (e.g.,initiated by the storage system) and a lower level process (e.g.,initiated by a storage controller of the storage system) may both beperformed.

To resolve various deficiencies of a traditional storage system,operations may be performed by higher level processes and not by thelower level processes. For example, the flash storage system may includeflash drives that do not include storage controllers that provide theprocess. Thus, the operating system of the flash storage system itselfmay initiate and control the process. This may be accomplished by adirect-mapped flash storage system that addresses data blocks within theflash drives directly and without an address translation performed bythe storage controllers of the flash drives.

The operating system of the flash storage system may identify andmaintain a list of allocation units across multiple flash drives of theflash storage system. The allocation units may be entire erase blocks ormultiple erase blocks. The operating system may maintain a map oraddress range that directly maps addresses to erase blocks of the flashdrives of the flash storage system.

Direct mapping to the erase blocks of the flash drives may be used torewrite data and erase data. For example, the operations may beperformed on one or more allocation units that include a first data anda second data where the first data is to be retained and the second datais no longer being used by the flash storage system. The operatingsystem may initiate the process to write the first data to new locationswithin other allocation units and erasing the second data and markingthe allocation units as being available for use for subsequent data.Thus, the process may only be performed by the higher level operatingsystem of the flash storage system without an additional lower levelprocess being performed by controllers of the flash drives.

Advantages of the process being performed only by the operating systemof the flash storage system include increased reliability of the flashdrives of the flash storage system as unnecessary or redundant writeoperations are not being performed during the process. One possiblepoint of novelty here is the concept of initiating and controlling theprocess at the operating system of the flash storage system. Inaddition, the process can be controlled by the operating system acrossmultiple flash drives. This is in contrast to the process beingperformed by a storage controller of a flash drive.

A storage system can consist of two storage array controllers that sharea set of drives for failover purposes, or it could consist of a singlestorage array controller that provides a storage service that utilizesmultiple drives, or it could consist of a distributed network of storagearray controllers each with some number of drives or some amount ofFlash storage where the storage array controllers in the networkcollaborate to provide a complete storage service and collaborate onvarious aspects of a storage service including storage allocation andgarbage collection.

FIG. 1C illustrates a third example system 117 for data storage inaccordance with some implementations. System 117 (also referred to as“storage system” herein) includes numerous elements for purposes ofillustration rather than limitation. It may be noted that system 117 mayinclude the same, more, or fewer elements configured in the same ordifferent manner in other implementations.

In one embodiment, system 117 includes a dual Peripheral ComponentInterconnect (‘PCI’) flash storage device 118 with separatelyaddressable fast write storage. System 117 may include a storagecontroller 119. In one embodiment, storage controller 119 may be a CPU,ASIC, FPGA, or any other circuitry that may implement control structuresnecessary according to the present disclosure. In one embodiment, system117 includes flash memory devices (e.g., including flash memory devices120 a-n), operatively coupled to various channels of the storage devicecontroller 119. Flash memory devices 120 a-n, may be presented to thecontroller 119 as an addressable collection of Flash pages, eraseblocks, and/or control elements sufficient to allow the storage devicecontroller 119 to program and retrieve various aspects of the Flash. Inone embodiment, storage device controller 119 may perform operations onflash memory devices 120A-N including storing and retrieving datacontent of pages, arranging and erasing any blocks, tracking statisticsrelated to the use and reuse of Flash memory pages, erase blocks, andcells, tracking and predicting error codes and faults within the Flashmemory, controlling voltage levels associated with programming andretrieving contents of Flash cells, etc.

In one embodiment, system 117 may include RAM 121 to store separatelyaddressable fast-write data. In one embodiment, RAM 121 may be one ormore separate discrete devices. In another embodiment, RAM 121 may beintegrated into storage device controller 119 or multiple storage devicecontrollers. The RAM 121 may be utilized for other purposes as well,such as temporary program memory for a processing device (e.g., a CPU)in the storage device controller 119.

In one embodiment, system 119 may include a stored energy device 122,such as a rechargeable battery or a capacitor. Stored energy device 122may store energy sufficient to power the storage device controller 119,some amount of the RAM (e.g., RAM 121), and some amount of Flash memory(e.g., Flash memory 120 a-120 n) for sufficient time to write thecontents of RAM to Flash memory. In one embodiment, storage devicecontroller 119 may write the contents of RAM to Flash Memory if thestorage device controller detects loss of external power.

In one embodiment, system 117 includes two data communications links 123a, 123 b. In one embodiment, data communications links 123 a, 123 b maybe PCI interfaces. In another embodiment, data communications links 123a, 123 b may be based on other communications standards (e.g.,HyperTransport, InfiniBand, etc.). Data communications links 123 a, 123b may be based on non-volatile memory express (‘NVMe’) or NVMe overfabrics (‘NVMf’) specifications that allow external connection to thestorage device controller 119 from other components in the storagesystem 117. It should be noted that data communications links may beinterchangeably referred to herein as PCI buses for convenience.

System 117 may also include an external power source (not shown), whichmay be provided over one or both data communications links 123 a, 123 b,or which may be provided separately. An alternative embodiment includesa separate Flash memory (not shown) dedicated for use in storing thecontent of RAM 121. The storage device controller 119 may present alogical device over a PCI bus which may include an addressablefast-write logical device, or a distinct part of the logical addressspace of the storage device 118, which may be presented as PCI memory oras persistent storage. In one embodiment, operations to store into thedevice are directed into the RAM 121. On power failure, the storagedevice controller 119 may write stored content associated with theaddressable fast-write logical storage to Flash memory (e.g., Flashmemory 120 a-n) for long-term persistent storage.

In one embodiment, the logical device may include some presentation ofsome or all of the content of the Flash memory devices 120 a-n, wherethat presentation allows a storage system including a storage device 118(e.g., storage system 117) to directly address Flash memory pages anddirectly reprogram erase blocks from storage system components that areexternal to the storage device through the PCI bus. The presentation mayalso allow one or more of the external components to control andretrieve other aspects of the Flash memory including some or all of:tracking statistics related to use and reuse of Flash memory pages,erase blocks, and cells across all the Flash memory devices; trackingand predicting error codes and faults within and across the Flash memorydevices; controlling voltage levels associated with programming andretrieving contents of Flash cells; etc.

In one embodiment, the stored energy device 122 may be sufficient toensure completion of in-progress operations to the Flash memory devices107 a-120 n stored energy device 122 may power storage device controller119 and associated Flash memory devices (e.g., 120 a-n) for thoseoperations, as well as for the storing of fast-write RAM to Flashmemory. Stored energy device 122 may be used to store accumulatedstatistics and other parameters kept and tracked by the Flash memorydevices 120 a-n and/or the storage device controller 119. Separatecapacitors or stored energy devices (such as smaller capacitors near orembedded within the Flash memory devices themselves) may be used forsome or all of the operations described herein.

Various schemes may be used to track and optimize the life span of thestored energy component, such as adjusting voltage levels over time,partially discharging the storage energy device 122 to measurecorresponding discharge characteristics, etc. If the available energydecreases over time, the effective available capacity of the addressablefast-write storage may be decreased to ensure that it can be writtensafely based on the currently available stored energy.

FIG. 1D illustrates a third example system 124 for data storage inaccordance with some implementations. In one embodiment, system 124includes storage controllers 125 a, 125 b. In one embodiment, storagecontrollers 125 a, 125 b are operatively coupled to Dual PCI storagedevices 119 a, 119 b and 119 c, 119 d, respectively. Storage controllers125 a, 125 b may be operatively coupled (e.g., via a storage network130) to some number of host computers 127 a-n.

In one embodiment, two storage controllers (e.g., 125 a and 125 b)provide storage services, such as a SCS) block storage array, a fileserver, an object server, a database or data analytics service, etc. Thestorage controllers 125 a, 125 b may provide services through somenumber of network interfaces (e.g., 126 a-d) to host computers 127 a-noutside of the storage system 124. Storage controllers 125 a, 125 b mayprovide integrated services or an application entirely within thestorage system 124, forming a converged storage and compute system. Thestorage controllers 125 a, 125 b may utilize the fast write memorywithin or across storage devices 119 a-d to journal in progressoperations to ensure the operations are not lost on a power failure,storage controller removal, storage controller or storage systemshutdown, or some fault of one or more software or hardware componentswithin the storage system 124.

In one embodiment, controllers 125 a, 125 b operate as PCI masters toone or the other PCI buses 128 a, 128 b. In another embodiment, 128 aand 128 b may be based on other communications standards (e.g.,HyperTransport, InfiniBand, etc.). Other storage system embodiments mayoperate storage controllers 125 a, 125 b as multi-masters for both PCIbuses 128 a, 128 b. Alternately, a PCI/NVMe/NVMf switchinginfrastructure or fabric may connect multiple storage controllers. Somestorage system embodiments may allow storage devices to communicate witheach other directly rather than communicating only with storagecontrollers. In one embodiment, a storage device controller 119 a may beoperable under direction from a storage controller 125 a to synthesizeand transfer data to be stored into Flash memory devices from data thathas been stored in RAM (e.g., RAM 121 of FIG. 1C). For example, arecalculated version of RAM content may be transferred after a storagecontroller has determined that an operation has fully committed acrossthe storage system, or when fast-write memory on the device has reacheda certain used capacity, or after a certain amount of time, to ensureimprove safety of the data or to release addressable fast-write capacityfor reuse. This mechanism may be used, for example, to avoid a secondtransfer over a bus (e.g., 128 a, 128 b) from the storage controllers125 a, 125 b. In one embodiment, a recalculation may include compressingdata, attaching indexing or other metadata, combining multiple datasegments together, performing erasure code calculations, etc.

In one embodiment, under direction from a storage controller 125 a, 125b, a storage device controller 119 a, 119 b may be operable to calculateand transfer data to other storage devices from data stored in RAM(e.g., RAM 121 of FIG. 1C) without involvement of the storagecontrollers 125 a, 125 b. This operation may be used to mirror datastored in one controller 125 a to another controller 125 b, or it couldbe used to offload compression, data aggregation, and/or erasure codingcalculations and transfers to storage devices to reduce load on storagecontrollers or the storage controller interface 129 a, 129 b to the PCIbus 128 a, 128 b.

A storage device controller 119 may include mechanisms for implementinghigh availability primitives for use by other parts of a storage systemexternal to the Dual PCI storage device 118. For example, reservation orexclusion primitives may be provided so that, in a storage system withtwo storage controllers providing a highly available storage service,one storage controller may prevent the other storage controller fromaccessing or continuing to access the storage device. This could beused, for example, in cases where one controller detects that the othercontroller is not functioning properly or where the interconnect betweenthe two storage controllers may itself not be functioning properly.

In one embodiment, a storage system for use with Dual PCI direct mappedstorage devices with separately addressable fast write storage includessystems that manage erase blocks or groups of erase blocks as allocationunits for storing data on behalf of the storage service, or for storingmetadata (e.g., indexes, logs, etc.) associated with the storageservice, or for proper management of the storage system itself. Flashpages, which may be a few kilobytes in size, may be written as dataarrives or as the storage system is to persist data for long intervalsof time (e.g., above a defined threshold of time). To commit data morequickly, or to reduce the number of writes to the Flash memory devices,the storage controllers may first write data into the separatelyaddressable fast write storage on one more storage devices.

In one embodiment, the storage controllers 125 a, 125 b may initiate theuse of erase blocks within and across storage devices (e.g., 118) inaccordance with an age and expected remaining lifespan of the storagedevices, or based on other statistics. The storage controllers 125 a,125 b may initiate garbage collection and data migration data betweenstorage devices in accordance with pages that are no longer needed aswell as to manage Flash page and erase block lifespans and to manageoverall system performance.

In one embodiment, the storage system 124 may utilize mirroring and/orerasure coding schemes as part of storing data into addressable fastwrite storage and/or as part of writing data into allocation unitsassociated with erase blocks. Erasure codes may be used across storagedevices, as well as within erase blocks or allocation units, or withinand across Flash memory devices on a single storage device, to provideredundancy against single or multiple storage device failures or toprotect against internal corruptions of Flash memory pages resultingfrom Flash memory operations or from degradation of Flash memory cells.Mirroring and erasure coding at various levels may be used to recoverfrom multiple types of failures that occur separately or in combination.

The embodiments depicted with reference to FIGS. 2A-G illustrate astorage cluster that stores user data, such as user data originatingfrom one or more user or client systems or other sources external to thestorage cluster. The storage cluster distributes user data acrossstorage nodes housed within a chassis, or across multiple chassis, usingerasure coding and redundant copies of metadata. Erasure coding refersto a method of data protection or reconstruction in which data is storedacross a set of different locations, such as disks, storage nodes orgeographic locations. Flash memory is one type of solid-state memorythat may be integrated with the embodiments, although the embodimentsmay be extended to other types of solid-state memory or other storagemedium, including non-solid state memory. Control of storage locationsand workloads are distributed across the storage locations in aclustered peer-to-peer system. Tasks such as mediating communicationsbetween the various storage nodes, detecting when a storage node hasbecome unavailable, and balancing I/Os (inputs and outputs) across thevarious storage nodes, are all handled on a distributed basis. Data islaid out or distributed across multiple storage nodes in data fragmentsor stripes that support data recovery in some embodiments. Ownership ofdata can be reassigned within a cluster, independent of input and outputpatterns. This architecture described in more detail below allows astorage node in the cluster to fail, with the system remainingoperational, since the data can be reconstructed from other storagenodes and thus remain available for input and output operations. Invarious embodiments, a storage node may be referred to as a clusternode, a blade, or a server.

The storage cluster may be contained within a chassis, i.e., anenclosure housing one or more storage nodes. A mechanism to providepower to each storage node, such as a power distribution bus, and acommunication mechanism, such as a communication bus that enablescommunication between the storage nodes are included within the chassis.The storage cluster can run as an independent system in one locationaccording to some embodiments. In one embodiment, a chassis contains atleast two instances of both the power distribution and the communicationbus which may be enabled or disabled independently. The internalcommunication bus may be an Ethernet bus, however, other technologiessuch as PCIe, InfiniBand, and others, are equally suitable. The chassisprovides a port for an external communication bus for enablingcommunication between multiple chassis, directly or through a switch,and with client systems. The external communication may use a technologysuch as Ethernet, InfiniBand, Fibre Channel, etc. In some embodiments,the external communication bus uses different communication bustechnologies for inter-chassis and client communication. If a switch isdeployed within or between chassis, the switch may act as a translationbetween multiple protocols or technologies. When multiple chassis areconnected to define a storage cluster, the storage cluster may beaccessed by a client using either proprietary interfaces or standardinterfaces such as network file system (‘NFS’), common internet filesystem (‘CIFS’), small computer system interface (‘SCSI’) or hypertexttransfer protocol (‘HTTP’). Translation from the client protocol mayoccur at the switch, chassis external communication bus or within eachstorage node. In some embodiments, multiple chassis may be coupled orconnected to each other through an aggregator switch. A portion and/orall of the coupled or connected chassis may be designated as a storagecluster. As discussed above, each chassis can have multiple blades, eachblade has a media access control (‘MAC’) address, but the storagecluster is presented to an external network as having a single clusterIP address and a single MAC address in some embodiments.

Each storage node may be one or more storage servers and each storageserver is connected to one or more non-volatile solid state memoryunits, which may be referred to as storage units or storage devices. Oneembodiment includes a single storage server in each storage node andbetween one to eight non-volatile solid state memory units, however thisone example is not meant to be limiting. The storage server may includea processor, DRAM and interfaces for the internal communication bus andpower distribution for each of the power buses. Inside the storage node,the interfaces and storage unit share a communication bus, e.g., PCIExpress, in some embodiments. The non-volatile solid state memory unitsmay directly access the internal communication bus interface through astorage node communication bus, or request the storage node to accessthe bus interface. The non-volatile solid state memory unit contains anembedded CPU, solid state storage controller, and a quantity of solidstate mass storage, e.g., between 2-32 terabytes (‘TB’) in someembodiments. An embedded volatile storage medium, such as DRAM, and anenergy reserve apparatus are included in the non-volatile solid statememory unit. In some embodiments, the energy reserve apparatus is acapacitor, super-capacitor, or battery that enables transferring asubset of DRAM contents to a stable storage medium in the case of powerloss. In some embodiments, the non-volatile solid state memory unit isconstructed with a storage class memory, such as phase change ormagnetoresistive random access memory (‘MRAM’) that substitutes for DRAMand enables a reduced power hold-up apparatus.

One of many features of the storage nodes and non-volatile solid statestorage is the ability to proactively rebuild data in a storage cluster.The storage nodes and non-volatile solid state storage can determinewhen a storage node or non-volatile solid state storage in the storagecluster is unreachable, independent of whether there is an attempt toread data involving that storage node or non-volatile solid statestorage. The storage nodes and non-volatile solid state storage thencooperate to recover and rebuild the data in at least partially newlocations. This constitutes a proactive rebuild, in that the systemrebuilds data without waiting until the data is needed for a read accessinitiated from a client system employing the storage cluster. These andfurther details of the storage memory and operation thereof arediscussed below.

FIG. 2A is a perspective view of a storage cluster 161, with multiplestorage nodes 150 and internal solid-state memory coupled to eachstorage node to provide network attached storage or storage areanetwork, in accordance with some embodiments. A network attachedstorage, storage area network, or a storage cluster, or other storagememory, could include one or more storage clusters 161, each having oneor more storage nodes 150, in a flexible and reconfigurable arrangementof both the physical components and the amount of storage memoryprovided thereby. The storage cluster 161 is designed to fit in a rack,and one or more racks can be set up and populated as desired for thestorage memory. The storage cluster 161 has a chassis 138 havingmultiple slots 142. It should be appreciated that chassis 138 may bereferred to as a housing, enclosure, or rack unit. In one embodiment,the chassis 138 has fourteen slots 142, although other numbers of slotsare readily devised. For example, some embodiments have four slots,eight slots, sixteen slots, thirty-two slots, or other suitable numberof slots. Each slot 142 can accommodate one storage node 150 in someembodiments. Chassis 138 includes flaps 148 that can be utilized tomount the chassis 138 on a rack. Fans 144 provide air circulation forcooling of the storage nodes 150 and components thereof, although othercooling components could be used, or an embodiment could be devisedwithout cooling components. A switch fabric 146 couples storage nodes150 within chassis 138 together and to a network for communication tothe memory. In an embodiment depicted in herein, the slots 142 to theleft of the switch fabric 146 and fans 144 are shown occupied by storagenodes 150, while the slots 142 to the right of the switch fabric 146 andfans 144 are empty and available for insertion of storage node 150 forillustrative purposes. This configuration is one example, and one ormore storage nodes 150 could occupy the slots 142 in various furtherarrangements. The storage node arrangements need not be sequential oradjacent in some embodiments. Storage nodes 150 are hot pluggable,meaning that a storage node 150 can be inserted into a slot 142 in thechassis 138, or removed from a slot 142, without stopping or poweringdown the system. Upon insertion or removal of storage node 150 from slot142, the system automatically reconfigures in order to recognize andadapt to the change. Reconfiguration, in some embodiments, includesrestoring redundancy and/or rebalancing data or load.

Each storage node 150 can have multiple components. In the embodimentshown here, the storage node 150 includes a printed circuit board 159populated by a CPU 156, i.e., processor, a memory 154 coupled to the CPU156, and a non-volatile solid state storage 152 coupled to the CPU 156,although other mountings and/or components could be used in furtherembodiments. The memory 154 has instructions which are executed by theCPU 156 and/or data operated on by the CPU 156. As further explainedbelow, the non-volatile solid state storage 152 includes flash or, infurther embodiments, other types of solid-state memory.

Referring to FIG. 2A, storage cluster 161 is scalable, meaning thatstorage capacity with non-uniform storage sizes is readily added, asdescribed above. One or more storage nodes 150 can be plugged into orremoved from each chassis and the storage cluster self-configures insome embodiments. Plug-in storage nodes 150, whether installed in achassis as delivered or later added, can have different sizes. Forexample, in one embodiment a storage node 150 can have any multiple of 4TB, e.g., 8 TB, 12 TB, 16 TB, 32 TB, etc. In further embodiments, astorage node 150 could have any multiple of other storage amounts orcapacities. Storage capacity of each storage node 150 is broadcast, andinfluences decisions of how to stripe the data. For maximum storageefficiency, an embodiment can self-configure as wide as possible in thestripe, subject to a predetermined requirement of continued operationwith loss of up to one, or up to two, non-volatile solid state storageunits 152 or storage nodes 150 within the chassis.

FIG. 2B is a block diagram showing a communications interconnect 171A-Fand power distribution bus 172 coupling multiple storage nodes 150.Referring back to FIG. 2A, the communications interconnect 171A-F can beincluded in or implemented with the switch fabric 146 in someembodiments. Where multiple storage clusters 161 occupy a rack, thecommunications interconnect 171A-F can be included in or implementedwith a top of rack switch, in some embodiments. As illustrated in FIG.2B, storage cluster 161 is enclosed within a single chassis 138.External port 176 is coupled to storage nodes 150 through communicationsinterconnect 171A-F, while external port 174 is coupled directly to astorage node. External power port 178 is coupled to power distributionbus 172. Storage nodes 150 may include varying amounts and differingcapacities of non-volatile solid state storage 152 as described withreference to FIG. 2A. In addition, one or more storage nodes 150 may bea compute only storage node as illustrated in FIG. 2B. Authorities 168are implemented on the non-volatile solid state storages 152, forexample as lists or other data structures stored in memory. In someembodiments the authorities are stored within the non-volatile solidstate storage 152 and supported by software executing on a controller orother processor of the non-volatile solid state storage 152. In afurther embodiment, authorities 168 are implemented on the storage nodes150, for example as lists or other data structures stored in the memory154 and supported by software executing on the CPU 156 of the storagenode 150. Authorities 168 control how and where data is stored in thenon-volatile solid state storages 152 in some embodiments. This controlassists in determining which type of erasure coding scheme is applied tothe data, and which storage nodes 150 have which portions of the data.Each authority 168 may be assigned to a non-volatile solid state storage152. Each authority may control a range of inode numbers, segmentnumbers, or other data identifiers which are assigned to data by a filesystem, by the storage nodes 150, or by the non-volatile solid statestorage 152, in various embodiments.

Every piece of data, and every piece of metadata, has redundancy in thesystem in some embodiments. In addition, every piece of data and everypiece of metadata has an owner, which may be referred to as anauthority. If that authority is unreachable, for example through failureof a storage node, there is a plan of succession for how to find thatdata or that metadata. In various embodiments, there are redundantcopies of authorities 168. Authorities 168 have a relationship tostorage nodes 150 and non-volatile solid state storage 152 in someembodiments. Each authority 168, covering a range of data segmentnumbers or other identifiers of the data, may be assigned to a specificnon-volatile solid state storage 152. In some embodiments theauthorities 168 for all of such ranges are distributed over thenon-volatile solid state storages 152 of a storage cluster. Each storagenode 150 has a network port that provides access to the non-volatilesolid state storage(s) 152 of that storage node 150. Data can be storedin a segment, which is associated with a segment number and that segmentnumber is an indirection for a configuration of a RAID (redundant arrayof independent disks) stripe in some embodiments. The assignment and useof the authorities 168 thus establishes an indirection to data.Indirection may be referred to as the ability to reference dataindirectly, in this case via an authority 168, in accordance with someembodiments. A segment identifies a set of non-volatile solid statestorage 152 and a local identifier into the set of non-volatile solidstate storage 152 that may contain data. In some embodiments, the localidentifier is an offset into the device and may be reused sequentiallyby multiple segments. In other embodiments the local identifier isunique for a specific segment and never reused. The offsets in thenon-volatile solid state storage 152 are applied to locating data forwriting to or reading from the non-volatile solid state storage 152 (inthe form of a RAID stripe). Data is striped across multiple units ofnon-volatile solid state storage 152, which may include or be differentfrom the non-volatile solid state storage 152 having the authority 168for a particular data segment.

If there is a change in where a particular segment of data is located,e.g., during a data move or a data reconstruction, the authority 168 forthat data segment should be consulted, at that non-volatile solid statestorage 152 or storage node 150 having that authority 168. In order tolocate a particular piece of data, embodiments calculate a hash valuefor a data segment or apply an inode number or a data segment number.The output of this operation points to a non-volatile solid statestorage 152 having the authority 168 for that particular piece of data.In some embodiments there are two stages to this operation. The firststage maps an entity identifier (ID), e.g., a segment number, inodenumber, or directory number to an authority identifier. This mapping mayinclude a calculation such as a hash or a bit mask. The second stage ismapping the authority identifier to a particular non-volatile solidstate storage 152, which may be done through an explicit mapping. Theoperation is repeatable, so that when the calculation is performed, theresult of the calculation repeatably and reliably points to a particularnon-volatile solid state storage 152 having that authority 168. Theoperation may include the set of reachable storage nodes as input. Ifthe set of reachable non-volatile solid state storage units changes theoptimal set changes. In some embodiments, the persisted value is thecurrent assignment (which is always true) and the calculated value isthe target assignment the cluster will attempt to reconfigure towards.This calculation may be used to determine the optimal non-volatile solidstate storage 152 for an authority in the presence of a set ofnon-volatile solid state storage 152 that are reachable and constitutethe same cluster. The calculation also determines an ordered set of peernon-volatile solid state storage 152 that will also record the authorityto non-volatile solid state storage mapping so that the authority may bedetermined even if the assigned non-volatile solid state storage isunreachable. A duplicate or substitute authority 168 may be consulted ifa specific authority 168 is unavailable in some embodiments.

With reference to FIGS. 2A and 2B, two of the many tasks of the CPU 156on a storage node 150 are to break up write data, and reassemble readdata. When the system has determined that data is to be written, theauthority 168 for that data is located as above. When the segment ID fordata is already determined the request to write is forwarded to thenon-volatile solid state storage 152 currently determined to be the hostof the authority 168 determined from the segment. The host CPU 156 ofthe storage node 150, on which the non-volatile solid state storage 152and corresponding authority 168 reside, then breaks up or shards thedata and transmits the data out to various non-volatile solid statestorage 152. The transmitted data is written as a data stripe inaccordance with an erasure coding scheme. In some embodiments, data isrequested to be pulled, and in other embodiments, data is pushed. Inreverse, when data is read, the authority 168 for the segment IDcontaining the data is located as described above. The host CPU 156 ofthe storage node 150 on which the non-volatile solid state storage 152and corresponding authority 168 reside requests the data from thenon-volatile solid state storage and corresponding storage nodes pointedto by the authority. In some embodiments the data is read from flashstorage as a data stripe. The host CPU 156 of storage node 150 thenreassembles the read data, correcting any errors (if present) accordingto the appropriate erasure coding scheme, and forwards the reassembleddata to the network. In further embodiments, some or all of these taskscan be handled in the non-volatile solid state storage 152. In someembodiments, the segment host requests the data be sent to storage node150 by requesting pages from storage and then sending the data to thestorage node making the original request.

In some systems, for example in UNIX-style file systems, data is handledwith an index node or inode, which specifies a data structure thatrepresents an object in a file system. The object could be a file or adirectory, for example. Metadata may accompany the object, as attributessuch as permission data and a creation timestamp, among otherattributes. A segment number could be assigned to all or a portion ofsuch an object in a file system. In other systems, data segments arehandled with a segment number assigned elsewhere. For purposes ofdiscussion, the unit of distribution is an entity, and an entity can bea file, a directory or a segment. That is, entities are units of data ormetadata stored by a storage system. Entities are grouped into setscalled authorities. Each authority has an authority owner, which is astorage node that has the exclusive right to update the entities in theauthority. In other words, a storage node contains the authority, andthat the authority, in turn, contains entities.

A segment is a logical container of data in accordance with someembodiments. A segment is an address space between medium address spaceand physical flash locations, i.e., the data segment number, are in thisaddress space. Segments may also contain meta-data, which enable dataredundancy to be restored (rewritten to different flash locations ordevices) without the involvement of higher level software. In oneembodiment, an internal format of a segment contains client data andmedium mappings to determine the position of that data. Each datasegment is protected, e.g., from memory and other failures, by breakingthe segment into a number of data and parity shards, where applicable.The data and parity shards are distributed, i.e., striped, acrossnon-volatile solid state storage 152 coupled to the host CPUs 156 (SeeFIGS. 2E and 2G) in accordance with an erasure coding scheme. Usage ofthe term segments refers to the container and its place in the addressspace of segments in some embodiments. Usage of the term stripe refersto the same set of shards as a segment and includes how the shards aredistributed along with redundancy or parity information in accordancewith some embodiments.

A series of address-space transformations takes place across an entirestorage system. At the top are the directory entries (file names) whichlink to an inode. Modes point into medium address space, where data islogically stored. Medium addresses may be mapped through a series ofindirect mediums to spread the load of large files, or implement dataservices like deduplication or snapshots. Medium addresses may be mappedthrough a series of indirect mediums to spread the load of large files,or implement data services like deduplication or snapshots. Segmentaddresses are then translated into physical flash locations. Physicalflash locations have an address range bounded by the amount of flash inthe system in accordance with some embodiments. Medium addresses andsegment addresses are logical containers, and in some embodiments use a128 bit or larger identifier so as to be practically infinite, with alikelihood of reuse calculated as longer than the expected life of thesystem. Addresses from logical containers are allocated in ahierarchical fashion in some embodiments. Initially, each non-volatilesolid state storage unit 152 may be assigned a range of address space.Within this assigned range, the non-volatile solid state storage 152 isable to allocate addresses without synchronization with othernon-volatile solid state storage 152.

Data and metadata is stored by a set of underlying storage layouts thatare optimized for varying workload patterns and storage devices. Theselayouts incorporate multiple redundancy schemes, compression formats andindex algorithms. Some of these layouts store information aboutauthorities and authority masters, while others store file metadata andfile data. The redundancy schemes include error correction codes thattolerate corrupted bits within a single storage device (such as a NANDflash chip), erasure codes that tolerate the failure of multiple storagenodes, and replication schemes that tolerate data center or regionalfailures. In some embodiments, low density parity check (‘LDPC’) code isused within a single storage unit. Reed-Solomon encoding is used withina storage cluster, and mirroring is used within a storage grid in someembodiments. Metadata may be stored using an ordered log structuredindex (such as a Log Structured Merge Tree), and large data may not bestored in a log structured layout.

In order to maintain consistency across multiple copies of an entity,the storage nodes agree implicitly on two things through calculations:(1) the authority that contains the entity, and (2) the storage nodethat contains the authority. The assignment of entities to authoritiescan be done by pseudo randomly assigning entities to authorities, bysplitting entities into ranges based upon an externally produced key, orby placing a single entity into each authority. Examples of pseudorandomschemes are linear hashing and the Replication Under Scalable Hashing(‘RUSH’) family of hashes, including Controlled Replication UnderScalable Hashing (‘CRUSH’). In some embodiments, pseudo-randomassignment is utilized only for assigning authorities to nodes becausethe set of nodes can change. The set of authorities cannot change so anysubjective function may be applied in these embodiments. Some placementschemes automatically place authorities on storage nodes, while otherplacement schemes rely on an explicit mapping of authorities to storagenodes. In some embodiments, a pseudorandom scheme is utilized to mapfrom each authority to a set of candidate authority owners. Apseudorandom data distribution function related to CRUSH may assignauthorities to storage nodes and create a list of where the authoritiesare assigned. Each storage node has a copy of the pseudorandom datadistribution function, and can arrive at the same calculation fordistributing, and later finding or locating an authority. Each of thepseudorandom schemes requires the reachable set of storage nodes asinput in some embodiments in order to conclude the same target nodes.Once an entity has been placed in an authority, the entity may be storedon physical devices so that no expected failure will lead to unexpecteddata loss. In some embodiments, rebalancing algorithms attempt to storethe copies of all entities within an authority in the same layout and onthe same set of machines.

Examples of expected failures include device failures, stolen machines,datacenter fires, and regional disasters, such as nuclear or geologicalevents. Different failures lead to different levels of acceptable dataloss. In some embodiments, a stolen storage node impacts neither thesecurity nor the reliability of the system, while depending on systemconfiguration, a regional event could lead to no loss of data, a fewseconds or minutes of lost updates, or even complete data loss.

In the embodiments, the placement of data for storage redundancy isindependent of the placement of authorities for data consistency. Insome embodiments, storage nodes that contain authorities do not containany persistent storage. Instead, the storage nodes are connected tonon-volatile solid state storage units that do not contain authorities.The communications interconnect between storage nodes and non-volatilesolid state storage units consists of multiple communicationtechnologies and has non-uniform performance and fault tolerancecharacteristics. In some embodiments, as mentioned above, non-volatilesolid state storage units are connected to storage nodes via PCIexpress, storage nodes are connected together within a single chassisusing Ethernet backplane, and chassis are connected together to form astorage cluster. Storage clusters are connected to clients usingEthernet or fiber channel in some embodiments. If multiple storageclusters are configured into a storage grid, the multiple storageclusters are connected using the Internet or other long-distancenetworking links, such as a “metro scale” link or private link that doesnot traverse the internet.

Authority owners have the exclusive right to modify entities, to migrateentities from one non-volatile solid state storage unit to anothernon-volatile solid state storage unit, and to add and remove copies ofentities. This allows for maintaining the redundancy of the underlyingdata. When an authority owner fails, is going to be decommissioned, oris overloaded, the authority is transferred to a new storage node.Transient failures make it non-trivial to ensure that all non-faultymachines agree upon the new authority location. The ambiguity thatarises due to transient failures can be achieved automatically by aconsensus protocol such as Paxos, hot-warm failover schemes, via manualintervention by a remote system administrator, or by a local hardwareadministrator (such as by physically removing the failed machine fromthe cluster, or pressing a button on the failed machine). In someembodiments, a consensus protocol is used, and failover is automatic. Iftoo many failures or replication events occur in too short a timeperiod, the system goes into a self-preservation mode and haltsreplication and data movement activities until an administratorintervenes in accordance with some embodiments.

As authorities are transferred between storage nodes and authorityowners update entities in their authorities, the system transfersmessages between the storage nodes and non-volatile solid state storageunits. With regard to persistent messages, messages that have differentpurposes are of different types. Depending on the type of the message,the system maintains different ordering and durability guarantees. Asthe persistent messages are being processed, the messages aretemporarily stored in multiple durable and non-durable storage hardwaretechnologies. In some embodiments, messages are stored in RAM, NVRAM andon NAND flash devices, and a variety of protocols are used in order tomake efficient use of each storage medium. Latency-sensitive clientrequests may be persisted in replicated NVRAM, and then later NAND,while background rebalancing operations are persisted directly to NAND.

Persistent messages are persistently stored prior to being transmitted.This allows the system to continue to serve client requests despitefailures and component replacement. Although many hardware componentscontain unique identifiers that are visible to system administrators,manufacturer, hardware supply chain and ongoing monitoring qualitycontrol infrastructure, applications running on top of theinfrastructure address virtualize addresses. These virtualized addressesdo not change over the lifetime of the storage system, regardless ofcomponent failures and replacements. This allows each component of thestorage system to be replaced over time without reconfiguration ordisruptions of client request processing, i.e., the system supportsnon-disruptive upgrades.

In some embodiments, the virtualized addresses are stored withsufficient redundancy. A continuous monitoring system correlateshardware and software status and the hardware identifiers. This allowsdetection and prediction of failures due to faulty components andmanufacturing details. The monitoring system also enables the proactivetransfer of authorities and entities away from impacted devices beforefailure occurs by removing the component from the critical path in someembodiments.

FIG. 2C is a multiple level block diagram, showing contents of a storagenode 150 and contents of a non-volatile solid state storage 152 of thestorage node 150. Data is communicated to and from the storage node 150by a network interface controller (‘NIC’) 202 in some embodiments. Eachstorage node 150 has a CPU 156, and one or more non-volatile solid statestorage 152, as discussed above. Moving down one level in FIG. 2C, eachnon-volatile solid state storage 152 has a relatively fast non-volatilesolid state memory, such as nonvolatile random access memory (‘NVRAM’)204, and flash memory 206. In some embodiments, NVRAM 204 may be acomponent that does not require program/erase cycles (DRAM, MRAM, PCM),and can be a memory that can support being written vastly more oftenthan the memory is read from. Moving down another level in FIG. 2C, theNVRAM 204 is implemented in one embodiment as high speed volatilememory, such as dynamic random access memory (DRAM) 216, backed up byenergy reserve 218. Energy reserve 218 provides sufficient electricalpower to keep the DRAM 216 powered long enough for contents to betransferred to the flash memory 206 in the event of power failure. Insome embodiments, energy reserve 218 is a capacitor, super-capacitor,battery, or other device, that supplies a suitable supply of energysufficient to enable the transfer of the contents of DRAM 216 to astable storage medium in the case of power loss. The flash memory 206 isimplemented as multiple flash dies 222, which may be referred to aspackages of flash dies 222 or an array of flash dies 222. It should beappreciated that the flash dies 222 could be packaged in any number ofways, with a single die per package, multiple dies per package (i.e.multichip packages), in hybrid packages, as bare dies on a printedcircuit board or other substrate, as encapsulated dies, etc. In theembodiment shown, the non-volatile solid state storage 152 has acontroller 212 or other processor, and an input output (I/O) port 210coupled to the controller 212. I/O port 210 is coupled to the CPU 156and/or the network interface controller 202 of the flash storage node150. Flash input output (I/O) port 220 is coupled to the flash dies 222,and a direct memory access unit (DMA) 214 is coupled to the controller212, the DRAM 216 and the flash dies 222. In the embodiment shown, theI/O port 210, controller 212, DMA unit 214 and flash I/O port 220 areimplemented on a programmable logic device (‘PLD’) 208, e.g., a fieldprogrammable gate array (FPGA). In this embodiment, each flash die 222has pages, organized as sixteen kB (kilobyte) pages 224, and a register226 through which data can be written to or read from the flash die 222.In further embodiments, other types of solid-state memory are used inplace of, or in addition to flash memory illustrated within flash die222.

Storage clusters 161, in various embodiments as disclosed herein, can becontrasted with storage arrays in general. The storage nodes 150 arepart of a collection that creates the storage cluster 161. Each storagenode 150 owns a slice of data and computing required to provide thedata. Multiple storage nodes 150 cooperate to store and retrieve thedata. Storage memory or storage devices, as used in storage arrays ingeneral, are less involved with processing and manipulating the data.Storage memory or storage devices in a storage array receive commands toread, write, or erase data. The storage memory or storage devices in astorage array are not aware of a larger system in which they areembedded, or what the data means. Storage memory or storage devices instorage arrays can include various types of storage memory, such as RAM,solid state drives, hard disk drives, etc. The storage units 152described herein have multiple interfaces active simultaneously andserving multiple purposes. In some embodiments, some of thefunctionality of a storage node 150 is shifted into a storage unit 152,transforming the storage unit 152 into a combination of storage unit 152and storage node 150. Placing computing (relative to storage data) intothe storage unit 152 places this computing closer to the data itself.The various system embodiments have a hierarchy of storage node layerswith different capabilities. By contrast, in a storage array, acontroller owns and knows everything about all of the data that thecontroller manages in a shelf or storage devices. In a storage cluster161, as described herein, multiple controllers in multiple storage units152 and/or storage nodes 150 cooperate in various ways (e.g., forerasure coding, data sharding, metadata communication and redundancy,storage capacity expansion or contraction, data recovery, and so on).

FIG. 2D shows a storage server environment, which uses embodiments ofthe storage nodes 150 and storage units 152 of FIGS. 2A-C. In thisversion, each storage unit 152 has a processor such as controller 212(see FIG. 2C), an FPGA (field programmable gate array), flash memory206, and NVRAM 204 (which is super-capacitor backed DRAM 216, see FIGS.2B and 2C) on a PCIe (peripheral component interconnect express) boardin a chassis 138 (see FIG. 2A). The storage unit 152 may be implementedas a single board containing storage, and may be the largest tolerablefailure domain inside the chassis. In some embodiments, up to twostorage units 152 may fail and the device will continue with no dataloss.

The physical storage is divided into named regions based on applicationusage in some embodiments. The NVRAM 204 is a contiguous block ofreserved memory in the storage unit 152 DRAM 216, and is backed by NANDflash. NVRAM 204 is logically divided into multiple memory regionswritten for two as spool (e.g., spool_region). Space within the NVRAM204 spools is managed by each authority 168 independently. Each deviceprovides an amount of storage space to each authority 168. Thatauthority 168 further manages lifetimes and allocations within thatspace. Examples of a spool include distributed transactions or notions.When the primary power to a storage unit 152 fails, onboardsuper-capacitors provide a short duration of power hold up. During thisholdup interval, the contents of the NVRAM 204 are flushed to flashmemory 206. On the next power-on, the contents of the NVRAM 204 arerecovered from the flash memory 206.

As for the storage unit controller, the responsibility of the logical“controller” is distributed across each of the blades containingauthorities 168. This distribution of logical control is shown in FIG.2D as a host controller 242, mid-tier controller 244 and storage unitcontroller(s) 246. Management of the control plane and the storage planeare treated independently, although parts may be physically co-locatedon the same blade. Each authority 168 effectively serves as anindependent controller. Each authority 168 provides its own data andmetadata structures, its own background workers, and maintains its ownlifecycle.

FIG. 2E is a blade 252 hardware block diagram, showing a control plane254, compute and storage planes 256, 258, and authorities 168interacting with underlying physical resources, using embodiments of thestorage nodes 150 and storage units 152 of FIGS. 2A-C in the storageserver environment of FIG. 2D. The control plane 254 is partitioned intoa number of authorities 168 which can use the compute resources in thecompute plane 256 to run on any of the blades 252. The storage plane 258is partitioned into a set of devices, each of which provides access toflash 206 and NVRAM 204 resources.

In the compute and storage planes 256, 258 of FIG. 2E, the authorities168 interact with the underlying physical resources (i.e., devices).From the point of view of an authority 168, its resources are stripedover all of the physical devices. From the point of view of a device, itprovides resources to all authorities 168, irrespective of where theauthorities happen to run. Each authority 168 has allocated or has beenallocated one or more partitions 260 of storage memory in the storageunits 152, e.g. partitions 260 in flash memory 206 and NVRAM 204. Eachauthority 168 uses those allocated partitions 260 that belong to it, forwriting or reading user data. Authorities can be associated withdiffering amounts of physical storage of the system. For example, oneauthority 168 could have a larger number of partitions 260 or largersized partitions 260 in one or more storage units 152 than one or moreother authorities 168.

FIG. 2F depicts elasticity software layers in blades 252 of a storagecluster, in accordance with some embodiments. In the elasticitystructure, elasticity software is symmetric, i.e., each blade's computemodule 270 runs the three identical layers of processes depicted in FIG.2F. Storage managers 274 execute read and write requests from otherblades 252 for data and metadata stored in local storage unit 152 NVRAM204 and flash 206. Authorities 168 fulfill client requests by issuingthe necessary reads and writes to the blades 252 on whose storage units152 the corresponding data or metadata resides. Endpoints 272 parseclient connection requests received from switch fabric 146 supervisorysoftware, relay the client connection requests to the authorities 168responsible for fulfillment, and relay the authorities' 168 responses toclients. The symmetric three-layer structure enables the storagesystem's high degree of concurrency. Elasticity scales out efficientlyand reliably in these embodiments. In addition, elasticity implements aunique scale-out technique that balances work evenly across allresources regardless of client access pattern, and maximizes concurrencyby eliminating much of the need for inter-blade coordination thattypically occurs with conventional distributed locking.

Still referring to FIG. 2F, authorities 168 running in the computemodules 270 of a blade 252 perform the internal operations required tofulfill client requests. One feature of elasticity is that authorities168 are stateless, i.e., they cache active data and metadata in theirown blades' 252 DRAMs for fast access, but the authorities store everyupdate in their NVRAM 204 partitions on three separate blades 252 untilthe update has been written to flash 206. All the storage system writesto NVRAM 204 are in triplicate to partitions on three separate blades252 in some embodiments. With triple-mirrored NVRAM 204 and persistentstorage protected by parity and Reed-Solomon RAID checksums, the storagesystem can survive concurrent failure of two blades 252 with no loss ofdata, metadata, or access to either.

Because authorities 168 are stateless, they can migrate between blades252. Each authority 168 has a unique identifier. NVRAM 204 and flash 206partitions are associated with authorities' 168 identifiers, not withthe blades 252 on which they are running in some. Thus, when anauthority 168 migrates, the authority 168 continues to manage the samestorage partitions from its new location. When a new blade 252 isinstalled in an embodiment of the storage cluster, the systemautomatically rebalances load by: partitioning the new blade's 252storage for use by the system's authorities 168, migrating selectedauthorities 168 to the new blade 252, starting endpoints 272 on the newblade 252 and including them in the switch fabric's 146 clientconnection distribution algorithm.

From their new locations, migrated authorities 168 persist the contentsof their NVRAM 204 partitions on flash 206, process read and writerequests from other authorities 168, and fulfill the client requeststhat endpoints 272 direct to them. Similarly, if a blade 252 fails or isremoved, the system redistributes its authorities 168 among the system'sremaining blades 252. The redistributed authorities 168 continue toperform their original functions from their new locations.

FIG. 2G depicts authorities 168 and storage resources in blades 252 of astorage cluster, in accordance with some embodiments. Each authority 168is exclusively responsible for a partition of the flash 206 and NVRAM204 on each blade 252. The authority 168 manages the content andintegrity of its partitions independently of other authorities 168.Authorities 168 compress incoming data and preserve it temporarily intheir NVRAM 204 partitions, and then consolidate, RAID-protect, andpersist the data in segments of the storage in their flash 206partitions. As the authorities 168 write data to flash 206, storagemanagers 274 perform the necessary flash translation to optimize writeperformance and maximize media longevity. In the background, authorities168 “garbage collect,” or reclaim space occupied by data that clientshave made obsolete by overwriting the data. It should be appreciatedthat since authorities' 168 partitions are disjoint, there is no needfor distributed locking to execute client and writes or to performbackground functions.

The embodiments described herein may utilize various software,communication and/or networking protocols. In addition, theconfiguration of the hardware and/or software may be adjusted toaccommodate various protocols. For example, the embodiments may utilizeActive Directory, which is a database based system that providesauthentication, directory, policy, and other services in a WINDOWS™environment. In these embodiments, LDAP (Lightweight Directory AccessProtocol) is one example application protocol for querying and modifyingitems in directory service providers such as Active Directory. In someembodiments, a network lock manager (‘NLM’) is utilized as a facilitythat works in cooperation with the Network File System (‘NFS’) toprovide a System V style of advisory file and record locking over anetwork. The Server Message Block (‘SMB’) protocol, one version of whichis also known as Common Internet File System (‘CIFS’), may be integratedwith the storage systems discussed herein. SMP operates as anapplication-layer network protocol typically used for providing sharedaccess to files, printers, and serial ports and miscellaneouscommunications between nodes on a network. SMB also provides anauthenticated inter-process communication mechanism. AMAZON™ S3 (SimpleStorage Service) is a web service offered by Amazon Web Services, andthe systems described herein may interface with Amazon S3 through webservices interfaces (REST (representational state transfer), SOAP(simple object access protocol), and BitTorrent). A RESTful API(application programming interface) breaks down a transaction to createa series of small modules. Each module addresses a particular underlyingpart of the transaction. The control or permissions provided with theseembodiments, especially for object data, may include utilization of anaccess control list (‘ACL’). The ACL is a list of permissions attachedto an object and the ACL specifies which users or system processes aregranted access to objects, as well as what operations are allowed ongiven objects. The systems may utilize Internet Protocol version 6(‘IPv6’), as well as IPv4, for the communications protocol that providesan identification and location system for computers on networks androutes traffic across the Internet. The routing of packets betweennetworked systems may include Equal-cost multi-path routing (‘ECMP’),which is a routing strategy where next-hop packet forwarding to a singledestination can occur over multiple “best paths” which tie for top placein routing metric calculations. Multi-path routing can be used inconjunction with most routing protocols, because it is a per-hopdecision limited to a single router. The software may supportMulti-tenancy, which is an architecture in which a single instance of asoftware application serves multiple customers. Each customer may bereferred to as a tenant. Tenants may be given the ability to customizesome parts of the application, but may not customize the application'scode, in some embodiments. The embodiments may maintain audit logs. Anaudit log is a document that records an event in a computing system. Inaddition to documenting what resources were accessed, audit log entriestypically include destination and source addresses, a timestamp, anduser login information for compliance with various regulations. Theembodiments may support various key management policies, such asencryption key rotation. In addition, the system may support dynamicroot passwords or some variation dynamically changing passwords.

FIG. 3A sets forth a diagram of a storage system 306 that is coupled fordata communications with a cloud services provider 302 in accordancewith some embodiments of the present disclosure. Although depicted inless detail, the storage system 306 depicted in FIG. 3A may be similarto the storage systems described above with reference to FIGS. 1A-1D andFIGS. 2A-2G. In some embodiments, the storage system 306 depicted inFIG. 3A may be embodied as a storage system that includes imbalancedactive/active controllers, as a storage system that includes balancedactive/active controllers, as a storage system that includesactive/active controllers where less than all of each controller'sresources are utilized such that each controller has reserve resourcesthat may be used to support failover, as a storage system that includesfully active/active controllers, as a storage system that includesdataset-segregated controllers, as a storage system that includesdual-layer architectures with front-end controllers and back-endintegrated storage controllers, as a storage system that includesscale-out clusters of dual-controller arrays, as well as combinations ofsuch embodiments.

In the example depicted in FIG. 3A, the storage system 306 is coupled tothe cloud services provider 302 via a data communications link 304. Thedata communications link 304 may be embodied as a dedicated datacommunications link, as a data communications pathway that is providedthrough the use of one or data communications networks such as a widearea network (‘WAN’) or local area network (‘LAN’), or as some othermechanism capable of transporting digital information between thestorage system 306 and the cloud services provider 302. Such a datacommunications link 304 may be fully wired, fully wireless, or someaggregation of wired and wireless data communications pathways. In suchan example, digital information may be exchanged between the storagesystem 306 and the cloud services provider 302 via the datacommunications link 304 using one or more data communications protocols.For example, digital information may be exchanged between the storagesystem 306 and the cloud services provider 302 via the datacommunications link 304 using the handheld device transfer protocol(‘HDTP’), hypertext transfer protocol (‘HTTP’), internet protocol(‘IP’), real-time transfer protocol (‘RTP’), transmission controlprotocol (‘TCP’), user datagram protocol (‘UDP’), wireless applicationprotocol (‘WAP’), or other protocol.

The cloud services provider 302 depicted in FIG. 3A may be embodied, forexample, as a system and computing environment that provides services tousers of the cloud services provider 302 through the sharing ofcomputing resources via the data communications link 304. The cloudservices provider 302 may provide on-demand access to a shared pool ofconfigurable computing resources such as computer networks, servers,storage, applications and services, and so on. The shared pool ofconfigurable resources may be rapidly provisioned and released to a userof the cloud services provider 302 with minimal management effort.Generally, the user of the cloud services provider 302 is unaware of theexact computing resources utilized by the cloud services provider 302 toprovide the services. Although in many cases such a cloud servicesprovider 302 may be accessible via the Internet, readers of skill in theart will recognize that any system that abstracts the use of sharedresources to provide services to a user through any data communicationslink may be considered a cloud services provider 302.

In the example depicted in FIG. 3A, the cloud services provider 302 maybe configured to provide a variety of services to the storage system 306and users of the storage system 306 through the implementation ofvarious service models. For example, the cloud services provider 302 maybe configured to provide services to the storage system 306 and users ofthe storage system 306 through the implementation of an infrastructureas a service (‘IaaS’) service model where the cloud services provider302 offers computing infrastructure such as virtual machines and otherresources as a service to subscribers. In addition, the cloud servicesprovider 302 may be configured to provide services to the storage system306 and users of the storage system 306 through the implementation of aplatform as a service (‘PaaS’) service model where the cloud servicesprovider 302 offers a development environment to application developers.Such a development environment may include, for example, an operatingsystem, programming-language execution environment, database, webserver, or other components that may be utilized by applicationdevelopers to develop and run software solutions on a cloud platform.Furthermore, the cloud services provider 302 may be configured toprovide services to the storage system 306 and users of the storagesystem 306 through the implementation of a software as a service(‘SaaS’) service model where the cloud services provider 302 offersapplication software, databases, as well as the platforms that are usedto run the applications to the storage system 306 and users of thestorage system 306, providing the storage system 306 and users of thestorage system 306 with on-demand software and eliminating the need toinstall and run the application on local computers, which may simplifymaintenance and support of the application. The cloud services provider302 may be further configured to provide services to the storage system306 and users of the storage system 306 through the implementation of anauthentication as a service (‘AaaS’) service model where the cloudservices provider 302 offers authentication services that can be used tosecure access to applications, data sources, or other resources. Thecloud services provider 302 may also be configured to provide servicesto the storage system 306 and users of the storage system 306 throughthe implementation of a storage as a service model where the cloudservices provider 302 offers access to its storage infrastructure foruse by the storage system 306 and users of the storage system 306.Readers will appreciate that the cloud services provider 302 may beconfigured to provide additional services to the storage system 306 andusers of the storage system 306 through the implementation of additionalservice models, as the service models described above are included onlyfor explanatory purposes and in no way represent a limitation of theservices that may be offered by the cloud services provider 302 or alimitation as to the service models that may be implemented by the cloudservices provider 302.

In the example depicted in FIG. 3A, the cloud services provider 302 maybe embodied, for example, as a private cloud, as a public cloud, or as acombination of a private cloud and public cloud. In an embodiment inwhich the cloud services provider 302 is embodied as a private cloud,the cloud services provider 302 may be dedicated to providing servicesto a single organization rather than providing services to multipleorganizations. In an embodiment where the cloud services provider 302 isembodied as a public cloud, the cloud services provider 302 may provideservices to multiple organizations. Public cloud and private clouddeployment models may differ and may come with various advantages anddisadvantages. For example, because a public cloud deployment involvesthe sharing of a computing infrastructure across different organization,such a deployment may not be ideal for organizations with securityconcerns, mission-critical workloads, uptime requirements demands, andso on. While a private cloud deployment can address some of theseissues, a private cloud deployment may require on-premises staff tomanage the private cloud. In still alternative embodiments, the cloudservices provider 302 may be embodied as a mix of a private and publiccloud services with a hybrid cloud deployment.

Although not explicitly depicted in FIG. 3A, readers will appreciatethat additional hardware components and additional software componentsmay be necessary to facilitate the delivery of cloud services to thestorage system 306 and users of the storage system 306. For example, thestorage system 306 may be coupled to (or even include) a cloud storagegateway. Such a cloud storage gateway may be embodied, for example, ashardware-based or software-based appliance that is located on premisewith the storage system 306. Such a cloud storage gateway may operate asa bridge between local applications that are executing on the storagearray 306 and remote, cloud-based storage that is utilized by thestorage array 306. Through the use of a cloud storage gateway,organizations may move primary iSCSI or NAS to the cloud servicesprovider 302, thereby enabling the organization to save space on theiron-premises storage systems. Such a cloud storage gateway may beconfigured to emulate a disk array, a block-based device, a file server,or other storage system that can translate the SCSI commands, fileserver commands, or other appropriate command into REST-space protocolsthat facilitate communications with the cloud services provider 302.

In order to enable the storage system 306 and users of the storagesystem 306 to make use of the services provided by the cloud servicesprovider 302, a cloud migration process may take place during whichdata, applications, or other elements from an organization's localsystems (or even from another cloud environment) are moved to the cloudservices provider 302. In order to successfully migrate data,applications, or other elements to the cloud services provider's 302environment, middleware such as a cloud migration tool may be utilizedto bridge gaps between the cloud services provider's 302 environment andan organization's environment. Such cloud migration tools may also beconfigured to address potentially high network costs and long transfertimes associated with migrating large volumes of data to the cloudservices provider 302, as well as addressing security concernsassociated with sensitive data to the cloud services provider 302 overdata communications networks. In order to further enable the storagesystem 306 and users of the storage system 306 to make use of theservices provided by the cloud services provider 302, a cloudorchestrator may also be used to arrange and coordinate automated tasksin pursuit of creating a consolidated process or workflow. Such a cloudorchestrator may perform tasks such as configuring various components,whether those components are cloud components or on-premises components,as well as managing the interconnections between such components. Thecloud orchestrator can simplify the inter-component communication andconnections to ensure that links are correctly configured andmaintained.

In the example depicted in FIG. 3A, and as described briefly above, thecloud services provider 302 may be configured to provide services to thestorage system 306 and users of the storage system 306 through the usageof a SaaS service model where the cloud services provider 302 offersapplication software, databases, as well as the platforms that are usedto run the applications to the storage system 306 and users of thestorage system 306, providing the storage system 306 and users of thestorage system 306 with on-demand software and eliminating the need toinstall and run the application on local computers, which may simplifymaintenance and support of the application. Such applications may takemany forms in accordance with various embodiments of the presentdisclosure. For example, the cloud services provider 302 may beconfigured to provide access to data analytics applications to thestorage system 306 and users of the storage system 306. Such dataanalytics applications may be configured, for example, to receivetelemetry data phoned home by the storage system 306. Such telemetrydata may describe various operating characteristics of the storagesystem 306 and may be analyzed, for example, to determine the health ofthe storage system 306, to identify workloads that are executing on thestorage system 306, to predict when the storage system 306 will run outof various resources, to recommend configuration changes, hardware orsoftware upgrades, workflow migrations, or other actions that mayimprove the operation of the storage system 306.

The cloud services provider 302 may also be configured to provide accessto virtualized computing environments to the storage system 306 andusers of the storage system 306. Such virtualized computing environmentsmay be embodied, for example, as a virtual machine or other virtualizedcomputer hardware platforms, virtual storage devices, virtualizedcomputer network resources, and so on. Examples of such virtualizedenvironments can include virtual machines that are created to emulate anactual computer, virtualized desktop environments that separate alogical desktop from a physical machine, virtualized file systems thatallow uniform access to different types of concrete file systems, andmany others.

For further explanation, FIG. 3B sets forth a diagram of a storagesystem 306 in accordance with some embodiments of the presentdisclosure. Although depicted in less detail, the storage system 306depicted in FIG. 3B may be similar to the storage systems describedabove with reference to FIGS. 1A-1D and FIGS. 2A-2G as the storagesystem may include many of the components described above.

The storage system 306 depicted in FIG. 3B may include storage resources308, which may be embodied in many forms. For example, in someembodiments the storage resources 308 can include nano-RAM or anotherform of nonvolatile random access memory that utilizes carbon nanotubesdeposited on a substrate. In some embodiments, the storage resources 308may include 3D crosspoint non-volatile memory in which bit storage isbased on a change of bulk resistance, in conjunction with a stackablecross-gridded data access array. In some embodiments, the storageresources 308 may include flash memory, including single-level cell(‘SLC’) NAND flash, multi-level cell (‘MLC’) NAND flash, triple-levelcell (‘TLC’) NAND flash, quad-level cell (‘QLC’) NAND flash, and others.In some embodiments, the storage resources 308 may include non-volatilemagnetoresistive random-access memory (‘MRAM’), including spin transfertorque (‘STT’) MRAM, in which data is stored through the use of magneticstorage elements. In some embodiments, the example storage resources 308may include non-volatile phase-change memory (‘PCM’) that may have theability to hold multiple bits in a single cell as cells can achieve anumber of distinct intermediary states. In some embodiments, the storageresources 308 may include quantum memory that allows for the storage andretrieval of photonic quantum information. In some embodiments, theexample storage resources 308 may include resistive random-access memory(‘ReRAM’) in which data is stored by changing the resistance across adielectric solid-state material. In some embodiments, the storageresources 308 may include storage class memory (‘SCM’) in whichsolid-state nonvolatile memory may be manufactured at a high densityusing some combination of sub-lithographic patterning techniques,multiple bits per cell, multiple layers of devices, and so on. Readerswill appreciate that other forms of computer memories and storagedevices may be utilized by the storage systems described above,including DRAM, SRAM, EEPROM, universal memory, and many others. Thestorage resources 308 depicted in FIG. 3A may be embodied in a varietyof form factors, including but not limited to, dual in-line memorymodules (‘DIMMs’), non-volatile dual in-line memory modules (‘NVDIMMs’),M.2, U.2, and others.

The example storage system 306 depicted in FIG. 3B may implement avariety of storage architectures. For example, storage systems inaccordance with some embodiments of the present disclosure may utilizeblock storage where data is stored in blocks, and each block essentiallyacts as an individual hard drive. Storage systems in accordance withsome embodiments of the present disclosure may utilize object storage,where data is managed as objects. Each object may include the dataitself, a variable amount of metadata, and a globally unique identifier,where object storage can be implemented at multiple levels (e.g., devicelevel, system level, interface level). Storage systems in accordancewith some embodiments of the present disclosure utilize file storage inwhich data is stored in a hierarchical structure. Such data may be savedin files and folders, and presented to both the system storing it andthe system retrieving it in the same format.

The example storage system 306 depicted in FIG. 3B may be embodied as astorage system in which additional storage resources can be addedthrough the use of a scale-up model, additional storage resources can beadded through the use of a scale-out model, or through some combinationthereof. In a scale-up model, additional storage may be added by addingadditional storage devices. In a scale-out model, however, additionalstorage nodes may be added to a cluster of storage nodes, where suchstorage nodes can include additional processing resources, additionalnetworking resources, and so on.

The storage system 306 depicted in FIG. 3B also includes communicationsresources 310 that may be useful in facilitating data communicationsbetween components within the storage system 306, as well as datacommunications between the storage system 306 and computing devices thatare outside of the storage system 306. The communications resources 310may be configured to utilize a variety of different protocols and datacommunication fabrics to facilitate data communications betweencomponents within the storage systems as well as computing devices thatare outside of the storage system. For example, the communicationsresources 310 can include fibre channel (‘FC’) technologies such as FCfabrics and FC protocols that can transport SCSI commands over FCnetworks. The communications resources 310 can also include FC overethernet (‘FCoE’) technologies through which FC frames are encapsulatedand transmitted over Ethernet networks. The communications resources 310can also include InfiniBand (‘IB’) technologies in which a switchedfabric topology is utilized to facilitate transmissions between channeladapters. The communications resources 310 can also include NVM Express(‘NVMe’) technologies and NVMe over fabrics (‘NVMeoF’) technologiesthrough which non-volatile storage media attached via a PCI express(‘PCIe’) bus may be accessed. The communications resources 310 can alsoinclude mechanisms for accessing storage resources 308 within thestorage system 306 utilizing serial attached SCSI (‘SAS’), serial ATA(‘SATA’) bus interfaces for connecting storage resources 308 within thestorage system 306 to host bus adapters within the storage system 306,internet small computer systems interface (‘iSCSI’) technologies toprovide block-level access to storage resources 308 within the storagesystem 306, and other communications resources that that may be usefulin facilitating data communications between components within thestorage system 306, as well as data communications between the storagesystem 306 and computing devices that are outside of the storage system306.

The storage system 306 depicted in FIG. 3B also includes processingresources 312 that may be useful in useful in executing computer programinstructions and performing other computational tasks within the storagesystem 306. The processing resources 312 may include one or moreapplication-specific integrated circuits (‘ASICs’) that are customizedfor some particular purpose as well as one or more central processingunits (‘CPUs’). The processing resources 312 may also include one ormore digital signal processors (‘DSPs’), one or more field-programmablegate arrays (‘FPGAs’), one or more systems on a chip (‘SoCs’), or otherform of processing resources 312. The storage system 306 may utilize thestorage resources 312 to perform a variety of tasks including, but notlimited to, supporting the execution of software resources 314 that willbe described in greater detail below.

The storage system 306 depicted in FIG. 3B also includes softwareresources 314 that, when executed by processing resources 312 within thestorage system 306, may perform various tasks. The software resources314 may include, for example, one or more modules of computer programinstructions that when executed by processing resources 312 within thestorage system 306 are useful in carrying out various data protectiontechniques to preserve the integrity of data that is stored within thestorage systems. Readers will appreciate that such data protectiontechniques may be carried out, for example, by system software executingon computer hardware within the storage system, by a cloud servicesprovider, or in other ways. Such data protection techniques can include,for example, data archiving techniques that cause data that is no longeractively used to be moved to a separate storage device or separatestorage system for long-term retention, data backup techniques throughwhich data stored in the storage system may be copied and stored in adistinct location to avoid data loss in the event of equipment failureor some other form of catastrophe with the storage system, datareplication techniques through which data stored in the storage systemis replicated to another storage system such that the data may beaccessible via multiple storage systems, data snapshotting techniquesthrough which the state of data within the storage system is captured atvarious points in time, data and database cloning techniques throughwhich duplicate copies of data and databases may be created, and otherdata protection techniques. Through the use of such data protectiontechniques, business continuity and disaster recovery objectives may bemet as a failure of the storage system may not result in the loss ofdata stored in the storage system.

The software resources 314 may also include software that is useful inimplementing software-defined storage (‘SDS’). In such an example, thesoftware resources 314 may include one or more modules of computerprogram instructions that, when executed, are useful in policy-basedprovisioning and management of data storage that is independent of theunderlying hardware. Such software resources 314 may be useful inimplementing storage virtualization to separate the storage hardwarefrom the software that manages the storage hardware.

The software resources 314 may also include software that is useful infacilitating and optimizing I/O operations that are directed to thestorage resources 308 in the storage system 306. For example, thesoftware resources 314 may include software modules that perform carryout various data reduction techniques such as, for example, datacompression, data deduplication, and others. The software resources 314may include software modules that intelligently group together I/Ooperations to facilitate better usage of the underlying storage resource308, software modules that perform data migration operations to migratefrom within a storage system, as well as software modules that performother functions. Such software resources 314 may be embodied as one ormore software containers or in many other ways.

Readers will appreciate that the various components depicted in FIG. 3Bmay be grouped into one or more optimized computing packages asconverged infrastructures. Such converged infrastructures may includepools of computers, storage and networking resources that can be sharedby multiple applications and managed in a collective manner usingpolicy-driven processes. Such converged infrastructures may minimizecompatibility issues between various components within the storagesystem 306 while also reducing various costs associated with theestablishment and operation of the storage system 306. Such convergedinfrastructures may be implemented with a converged infrastructurereference architecture, with standalone appliances, with a softwaredriven hyper-converged approach, or in other ways.

Readers will appreciate that the storage system 306 depicted in FIG. 3Bmay be useful for supporting various types of software applications. Forexample, the storage system 306 may be useful in supporting artificialintelligence applications, database applications, DevOps projects,electronic design automation tools, event-driven software applications,high performance computing applications, simulation applications,high-speed data capture and analysis applications, machine learningapplications, media production applications, media serving applications,picture archiving and communication systems (‘PACS’) applications,software development applications, and many other types of applicationsby providing storage resources to such applications.

For further explanation, FIG. 3C sets forth diagrams of storage systems320 and 330 implementing storage efficiency driven migration inaccordance with some embodiments of the present disclosure. Storagesystems 320 and 330 may each implement data storage features describedabove with reference to FIGS. 1A-1D, 2A-2G, 3A, and 3B, as storagesystems 320 and 330 may include some or all of the components describedabove—in addition to components, modules, or logic for implementingfeatures of storage efficiency driven data migration.

In some computer environments, different storage systems may servicedifferent types of workloads, where similar workload types may generatesimilar type data. Further, in some cases, data of a similar type may bereduced through deduplication or through compression or through someother technique better, or with higher resulting storage spaceefficiency, than data of dissimilar types. For example, storage system320 may service one or more workloads that generate one type of data,depicted as data 324 stored within data store 322, and one or moreworkloads that generate a different type of data, depicted as data 328stored within data store 326. As one example, data 324 may be video dataand data 326 may be web analytics data within a database, and the datastore may be a virtual storage volume, a physical storage device, orsome other type of data store.

Similarly, storage system 330 may service one or more workloads thatgenerate one type of data, depicted as data 334 stored within data store332, and one or more workloads that generate a different type of data,depicted as data 338 stored within data store 336. In this example, thetype of data for data 334 is similar to the type of data for data 324,and the type of data for data 338 is similar to the type of data fordata 328.

Further in this example, because of the lack of similarity between datatypes for data 324 and data 328 within storage system 320, anapplication of a technique to reduce storage capacity applied across alldata stored within all data stores of storage system 320 may havelimited or marginal results. However, if a technique to reduce storagecapacity were applied to data 324 and data 334, then because of asimilarity in the types of data for data 324 and data 334, the techniqueto reduce storage capacity would produce greater reductions in storagecapacity than if the technique to reduce storage capacity were appliedto data 324 and data 328. Therefore, if data 324 were migrated tostorage system 330 or if data 334 were migrated to storage system 320,then the combined footprint of storage space used by both data 324 and334 would be smaller than if no migration were performed. Similarly, ifdata 328 were migrated to storage system 330 or if data 338 weremigrated to storage system 320, then the combined footprint of storagespace used by both data 328 and 338 would be smaller than if nomigration were performed. While in this example all of data 334 may bemigrated to improve storage space usage, in other examples, one or moreportions of data 334 may be migrated, where the one or more portions maybe sufficient to satisfy a threshold level of storage space usagereduction. In other words, in some examples, less than the entire amountof similar data may be migrated, and the reasons may include limitedbandwidth, limited computing resources to perform the migration, or anexpected increase in resource utilization that may be hampered by amigration of a large quantity of data.

Because of the improvements to the reduction to storage use that wouldresult from considering data 324 and data 334 together when applying atechnique for reducing storage capacity, where data 324 and data 334 arestored, respectively, on different storage systems 320 and 330, if data334 is migrated to storage system 320, or if data 324 is migrated tostorage system 330, then the total storage requirements for data 324 anddata 334 are smaller than if data 324 and data 334 are stored, as theypresently are, on different storage systems. The bottom half of FIG. 3Cdepicts the state of storage system 320 and storage system 330subsequent to migrating data 334 from storage system 330 to storagesystem 320 and migrating data 328 from storage system 320 to storagesystem 330. Further, in general, data selected to be migrated may becondensed, compressed, or deduplicated prior to migration, therebyreducing a quantity of data being transmitted over a network orcommunication link.

As described further below, in some examples, detection of a possibilityfor reducing overall storage usage across multiple systems based on amigration of similar data may be described within a notificationprovided to a user. For example, a data management console may include auser interface that may display an alert, or some other user interfaceelement describing benefits to migrating data between storage systems,where the benefits may include reduced overall storage usage, loadbalancing improvements, or other implications from migrating data. Inthis example, a user may also be notified of resources that may beconsumed in migrating the data, or of a timeline or schedule to completethe migration, where a user may then authorize the migration of data ornot authorize the migration of data. In short, a user may simply click abutton to initiate a migration of similar data to reduce overall storagecapacity usage—without deleting data or making data less accessible.

In different embodiments, described in greater detail below, storagesystem 320 may generate or calculate a set of deduplication hashes fordata stored within each of the data stores within storage system 320.Further, storage system 320 may determine an expected amount of storagecapacity reduction based on the calculated set of deduplication hashesif deduplication were applied to data 324 and data 328. To determinewhether or not a data migration would result in reduced storagecapacity, storage system 320 may receive or request a set ofdeduplication hashes from one or more other storage systems, which inthis example includes storage system 330. Given the one or more sets ofdeduplication hashes from other systems, storage system 320 may comparethe set of deduplication hashes for locally stored data against the oneor more sets of deduplication hashes for data stored on the one or moreother storage systems. In this way, storage system 320 may determinewhich combinations of data using a deduplication technique correspond tothe greatest data storage reductions, or some reduction greater than athreshold amount of data storage reduction, and determine one or moremigrations of data to be able to apply the deduplication technique to agiven combination of data.

In other examples, instead of, or in addition to, a storage systemdetermining to migrate data, individual storage systems may communicatewith a data management service, where the data management serviceprovides a user interface for managing data stored across the multiplestorage systems, and where the data management service communicates withone or more managed storage systems to determine whether or not amigration of data would result in an overall reduction in data storageusage. In one example, the data management service may be implemented asa cloud-based service, where the storage systems may either becloud-based, physically or virtually, or implemented within a localcomputing environment, physically or virtually.

While in this example, it is beneficial to swap data 328 for data 334 orswap data 324 for data 338—in other words, two migrations would beperformed to achieve a swap—in other examples, a single migration ofdata may be identified, where the single migration of data itself issufficient to achieve a reduction of storage space usage. In otherexamples, where a greater number of storage systems are present, theremay be multiple migrations of data from multiple sources of storagesystems onto a target storage system to achieve reductions is storagespace based on improving the performance of a data reduction techniqueas applied to similar data.

In this way, storage efficiency driven migration may provide anadvantage of a smaller overall storage usage across multiple storagesystems after migration of similar data, where the multiple storagesystems may be distinct or independent from one another.

For further explanation, FIG. 3D sets forth diagrams of storage systems350 and 354A-354N implementing storage efficiency driven migration inaccordance with some embodiments of the present disclosure. Storagesystems 350 and 354A-354N may each implement data storage featuresdescribed above with reference to FIGS. 1A-1D, 2A-2G, and 3A-3C, asstorage systems 320 and 330 may include some or all of the componentsdescribed above—in addition to components, modules, or logic forimplementing features of storage efficiency driven data migration.

Storage system 350 may appear to a client device to be a single storagesystem providing a single unified storage space, where storage system350 may invisibly include multiple storage systems that may be directlyconnected to each other or connected over a network. In other words, theindividual storage systems 354A-354N are scaled out to appear as alarger, cohesive storage system 350. Further, any given storage system354A-354N may include a respective storage array, where an I/O operationreceived by storage system 350 may be relayed to any given storagesystem 354A-354N. As depicted in FIG. 3D, storage system 350 may includemultiple storage systems 354A-354N, where each of the multiple storagesystems 354A-354N may include a distinct and independent storage arraythat may communicate over network 352. Further, for each storage system354A-354N, each corresponding storage array may further provide a useraccess to one or more data stores or data volumes, depicted as volumes356A-356M within storage system 354A and volumes 358A-358P withinstorage system 354N. In this example, computing device(s) 340 maycommunicate directly to storage system 350, or computing device(s) 342may communicate with storage system 350 over network 344.

In this example, it may be that any given volume stored among storagesystem 354A-354N within storage system 350 is stored on a single storagesystem. As such, storage efficiency driven migration may be implementedbetween any two or more storage systems within storage system 350similarly to the implementation, described above with reference to FIG.3C, of storage efficiency driven migration between storage system 320and storage system 330. In short, the scope of data reduction techniquesmay be an individual storage system, and therefore, if data that isoutside the scope of a particular storage system because the data isstored on a different storage system is moved from the different storagesystem to the particular storage system, the overall data storage usedby the migrated data and the data on the particular storagesystem—subsequent to application of one or more data reductiontechniques on the migrated data and the data on the particularstorage—is less than prior to the migration. As described above, in somecases, an entire volume may be migrated, and in other cases, less thanan entire volume may be migrated.

Further, in the course of servicing I/O operations, storage system 350may migrate volumes for various reasons, including balancing networkactivity, workload balancing, among other reasons described below withreference to FIG. 9 . In this context, storage system 350 may determinethat migrating a volume 356A from storage system 354A to storage system354N may improve workload balance or network traffic. However, ifstorage system 350 determines that such a migration would result ingreater use of storage space resulting from a data reduction techniquebeing unable to generate similar data reduction results, then storagesystem 350 may determine that the cost of greater storage space usage—asmeasured across the multiple storage systems—outweighs the benefits of amove for other reasons, and consequently, storage system 350 may abortthe data migration or determine not to migrate the data. In a conversescenario, storage system 350 may, according to implementations ofstorage efficiency driven migration, determine to prioritize migrationof data between storage systems due to storage capacity constraints evenif a consequence is poorer performance with regard to other systemmetrics, such as network latency or I/O operations handled per unittime, or some other metric. In other words, because storage capacity maybe reaching a maximum capacity or critically low capacity, other systemactivities for improving other metrics are deprioritized relative tostorage efficiency driven migration to avoid running out of storagecapacity.

In other examples, storage system 350, instead of migrating datasubsequent to storage, may select a storage system among storage systems354A-354N in which to store incoming I/O operation data based at leastin part on relative improvements in storage space utilization fromapplying a data reduction technique to the incoming I/O operation datawith previously stored data.

For further explanation, FIG. 3E sets forth a flow chart illustrating anexample method for synchronizing a plurality of storage systems 354A and354B according to some embodiments of the present disclosure. Theexample method depicted in FIG. 3E includes two storage systems 354A and354B, labeled as a leader storage system 354A and a follower storagesystem 354B. Although depicted in less detail, the storage systems 354Aand 354B depicted in FIG. 3E may be similar to the storage arrays andstorage systems described above with reference to FIGS. 1-3D, thestorage clusters described above with reference to FIGS. 1-3D, or insome other way.

The designation of one storage system as the ‘leader’ and anotherstorage system as the ‘follower’ may refer to the respectiverelationships of each storage system for the purposes of synchronouslyreplicating data across the storage systems. In such an example, and aswill be described in greater detail below, the leader storage system354A may be responsible for performing some processing of an incomingI/O operation and passing such information along to the follower storagesystem 354B, acknowledging the completion of a synchronously replicatedI/O operation to the issuer of the I/O operation, or performing othertasks that are not required of the follower storage system 354B. Theleader storage system 354A may be responsible for performing tasks thatare not required of the follower storage system 354B for all incomingI/O operations or, alternatively, the leader-follower relationship maybe specific to only a subset of the I/O operations that are received byeither storage system. For example, the leader-follower relationship maybe specific to I/O operations that are directed towards a first volume,a first group of volumes, a first group of logical addresses, a firstgroup of physical addresses, or some other logical or physicaldelineator. In such a way, a first storage system may serve as theleader storage system for I/O operations directed to a first set ofvolumes (or other delineator) while a second storage system may serve asthe leader storage system for I/O operations directed to a second set ofvolumes (or other delineator). The example method depicted in FIG. 3Edepicts an embodiment where synchronizing a plurality of storage systems354A and 354B occurs in response to the receipt of an I/O operation bythe leader storage system 354A, although synchronizing a plurality ofstorage systems 354A and 354B may also be carried out in response to thereceipt of an I/O operation by the follower storage system 354B, as willbe described in greater detail below.

In this example method for synchronizing a plurality of storage systems,data corresponding to I/O operations that are directed towards aparticular volume, set of volumes, or other some other delineator, maybe considered a dataset that is synchronously replicated across theplurality of storage systems. As described below with reference to FIG.3F, a dataset that is synchronously replicated across storage systemsmay be expanded to included additional storage systems among which datais synchronously replicated, where the additional storage systems arethen considered together when implementing storage efficiency drivenmigration.

The example method depicted in FIG. 3E includes receiving (366), by theleader storage system 354A, an I/O operation 364. The I/O operation 364may be embodied, for example, as a request to write data to a locationwithin the storage system 350, as a request to copy data from a firstlocation within the storage system 350 to a second location within thestorage system 350, as a request to take a snapshot of a portion of thestorage system 350 and store such a snapshot within the storage system350, or as some other operation that results in a change to some portionof storage resources within the storage system 350. In the examplemethod depicted in FIG. 3E, the I/O operation 364 is issued by a host362 that may be embodied, for example, as an application that isexecuting on a virtual machine, as an application that is executing on acomputing device that is connected to the storage system 350, or as someother entity configured to access the storage system 350.

The example method depicted in FIG. 3E also includes generating (368),by the leader storage system 354A, I/O processing information 370. TheI/O processing information 370 may be embodied, for example, assystem-level information that is used to describe an I/O operation thatis to be performed by a storage system. The leader storage system 354Amay generate (368) I/O processing information 370 by processing the I/Ooperation 364 just enough to figure out what should happen in order toservice the I/O operation 364. For example, the leader storage system354A may determine whether some ordering of the execution of the I/Ooperation 364 relative to other I/O operations is required to produce anequivalent result on each storage system. Consider an example in whichthe I/O operation 364 is embodied as a request to take a snapshot of aparticular volume that is replicated on each storage system 354A and354B. In such an example, if three write operations (write A, write B,write C) that were directed to the particular volume have been servicedby the leader storage system 354A, the follower storage system 354B willalso need to service the same three write operations before servicingthe I/O operation 364 (i.e., the request to take a snapshot of theparticular volume that is replicated on each storage system 354A and354B in order for the snapshot taken by the leader storage system 354Ato match the snapshot taken by the follower storage system 354B. In suchan example, the I/O processing information 370 generated (368) by theleader storage system 354A may include information indicating that thefollower storage system 354B should complete the execution of write A,write B, and write C before servicing the I/O operation 364.

The example method depicted in FIG. 3E also includes sending (372), fromthe leader storage system 354A to the follower storage system 354B, theI/O processing information 370 along with any I/O payload 384 that isassociated with the I/O operation 364. The I/O payload 384 may beembodied, for example, as data that is to be written to storage withinthe storage system 350 when the I/O operation 364 is embodied as arequest to write data to the storage system 350. In such an example,because the I/O operation was received (366) by the leader storagesystem 354A, the follower storage system 354B has not received the I/Opayload 384 associated with the I/O operation 364. In the example methoddepicted in FIG. 3E, the I/O processing information 370 and the I/Opayload 384 that is associated with the I/O operation 364 may be sent(372) from the leader storage system 354A to the follower storage system354B via a data communications network that couples the leader storagesystem 354A to the follower storage system 354B, via a datacommunications link, for example a dedicated data communications link,that couples the leader storage system 354A to the follower storagesystem 354B, or via some other mechanism.

The example method depicted in FIG. 3E also includes receiving (386), bythe follower storage system 354B, I/O processing information 370 and I/Opayload 384 from the leader storage system 354A. The follower storagesystem 354B may receive (386) the I/O processing information 370 and I/Opayload 384 from the leader storage system 354A, for example, via one ormore messages that are sent from the leader storage system 354A to thefollower storage system 354B. The one or more messages may be sent fromthe leader storage system 354A to the follower storage system 354B viaone or more dedicated data communications links between the two storagesystems 354A and 354B, by the leader storage system 354A writing themessage to a predetermined memory location (e.g., the location of aqueue) on the follower storage system 354B using RDMA or a similarmechanism, or in other ways.

The example method depicted in FIG. 3E also includes servicing (388) theI/O operation 364 on the follower storage system 354B. In the examplemethod depicted in FIG. 3E, the follower storage system 354B may service(388) the I/O operation 364 by completing the I/O operation 364 usingthe I/O processing information 370 and the I/O payload 384 that wasreceived from the leader storage system 354A. In such an example, theI/O operation 364 may be considered to have been completed andsuccessfully serviced, for example, when the I/O payload 384 has beencommitted to persistent storage within the follower storage system 354B.

The example method depicted in FIG. 3E also includes acknowledging(390), by the follower storage system 354B, completion of the I/Ooperation 364 to the leader storage system 354A. The follower storagesystem 354B may acknowledge (390) completion of the I/O operation 364 tothe leader storage system 354A, for example, through the use of one ormore messages sent from the follower storage system 354B to the leaderstorage system 354A. Such messages may include, for example, informationidentifying the particular I/O operation 364 that was completed as wellas any additional information useful in acknowledging (390) thecompletion of the I/O operation 364 by the follower storage system 354B.In the example method depicted in FIG. 3E, acknowledging (390)completion of the I/O operation 364 to the leader storage system 354A isillustrated by the follower storage system 354B issuing anacknowledgment 392 message to the leader storage system 354A.

The example method depicted in FIG. 3E also includes servicing (374), bythe leader storage system 354A, the I/O operation 364 on the leaderstorage system 354A. In the example method depicted in FIG. 3E, theleader storage system 354A may service (374) the I/O operation 364 bycompleting the I/O operation 364 using the I/O processing information370 and the I/O payload 384. In such an example, the I/O operation 364may be considered to have been completed and successfully serviced, forexample, when the I/O payload 384 has been committed to persistentstorage within the leader storage system 354A.

The example method depicted in FIG. 3E also includes determining (378),by the leader storage system 354A, whether the I/O operation 364 hasbeen serviced on the follower storage system 354B. The leader storagesystem 354A may determine (378) whether the I/O operation 364 has beenserviced on the follower storage system 354B, for example, bydetermining whether the leader storage system 354A has received anacknowledgment message or other message from the follower storage system354B indicating that the follower storage system 354B has completedservicing the I/O operation 364. In such an example, if the leaderstorage system 354A affirmatively (380) determines that the I/Ooperation 364 has been serviced by the follower storage system 354B, theleader storage system 354A may proceed by acknowledging (382) thecompletion of the I/O operation 364 to the host 362 that initiated theI/O operation 364. If the leader storage system 354A determines that theI/O operation 364 has not (376) been serviced by the follower storagesystem 354B, however, the leader storage system 354A may not yetacknowledge (382) the completion of the I/O operation 364 to the host362 that initiated the I/O operation 364 as the storage system 350 mayonly acknowledge (382) the completion of the I/O operation 364 to thehost 362 that initiated the I/O operation 364 when the I/O operation 364has been successfully serviced on both storage systems 354A and 354B. Inthe example method depicted in FIG. 3E, acknowledging (382) completionof the I/O operation 364 may be carried out through the use of one ormore acknowledgement 394 messages that are sent from the leader storagesystem 354A to the host 362 or via some other appropriate mechanism.

Readers will appreciate that once the I/O processing information 370 andany associated I/O payload 384 has been received (386) by the followerstorage system 354B, each storage system 354A and 354B may beginprocessing the I/O operation 364 independently. As such, it is possiblethat the follower storage system 354B may even service (388) the I/Ooperation 364 and acknowledge (390) completion of the I/O operation 364to the leader storage system 354A prior to the leader storage system354A servicing (374) the I/O operation 364. As such, the onlyrequirement that must be satisfied before the leader storage system 354Aacknowledges (382) completion of the I/O operation 364 to the host 362is that the leader storage system 354A has confirmed that both storagesystems 354A and 354B have successfully completed servicing the I/Ooperation 364. There is no requirement that one storage system completesservicing the I/O operation before the other storage system completesservicing the I/O operation.

Readers will further appreciate that although the example depicted inFIG. 3E includes the leader storage system 354A generating (368) I/Oprocessing information 370 and sending (372) the I/O processinginformation 370 along with any I/O payload 384 that is associated withthe I/O operation 364 to the follower storage system 354B, inalternative embodiments the leader storage system 354A may simplyforward the I/O operation 364 to the follower storage system 354B. Suchan embodiment may require each storage system 354A and 354B to reproducework done by the other storage system, but such an embodiment maydesirable for various reasons.

For further explanation, FIG. 3F sets forth a diagram of storage system350, where storage system 350 includes storage systems 354A-354N, andwhere storage systems 350 and 354A-354N implement storage efficiencydriven migration in accordance with some embodiments of the presentdisclosure. Storage systems 350 and 354A-354N may each implement datastorage features described above with reference to FIGS. 1A-1D, 2A-2G,and 3A-3E, as storage systems 320 and 330 may include some or all of thecomponents described above—in addition to components, modules, or logicfor implementing features of storage efficiency driven data migration.In this example, storage system 354A includes volumes 397A and 397M,storage system 354B includes volume 398A and 397M, and storage system354N includes volumes 399A and 399P.

FIG. 3F depicts a dataset, dataset 395, where dataset 395 representsdata that is synchronously replicated across multiple storage systems asdescribed above with reference to FIG. 3E. In this example, dataset 395represents synchronously replicated data across storage systems 354A and354B, as depicted in FIG. 3E. However, in some examples, if data storedon storage system 354N is similar to the data within dataset 395 that isbeing synchronously replicated, then if dataset 395 is extended, orstretched, to include storage system 354N, then the synchronouslyreplicated data within dataset 395 becomes available for application ofone or more data reduction techniques as applied to data within dataset395 on storage system 354N as well as data stored on storage system 354Nthat is not within dataset 395. In other words, by extending the scopeof the synchronously replicated data within dataset 395, additionalstorage capacity reductions may be possible.

Further, a storage system may be identified as being a candidate forextending a dataset based on factors that include one or more of:servicing similar workload types, storing similar data, or a quantity ofmatching deduplication hashes. Further, extension of a dataset may beconsidered according to factors described below similar to determiningwhether data on different storage systems is similar enough to satisfy athreshold level of similarity, where if data on a potential storagesystem satisfies the threshold level of similarity to data within adataset on other storage systems, then in response a dataset may beextended from the other storage systems to include the potential storagesystem.

For further explanation, FIG. 4 sets forth a flow chart illustrating anexample method for storage efficiency driven migration according to someembodiments of the present disclosure. Although depicted in less detail,the storage system (402) depicted in FIG. 4 may be similar to thestorage systems described above with reference to FIGS. 1A-1D, FIGS.2A-2G, FIGS. 3A-3C, or any combination thereof. Further, the storagesystem depicted in FIG. 4 may include the same, fewer, or additionalcomponents as the storage systems described above.

The example method depicted in FIG. 4 includes determining (404) a levelof similarity between first data 452 stored on a first storage system402 and second data 456 stored on second storage system 454. Determining(404) a level of similarity between first data 452 and second data 456may be implemented using different techniques. In some cases, a level ofsimilarity may be represented as a percentage value indicating a percentsimilar. One technique includes applying a deduplication algorithm anddetermining a level of similarity between data as described below withreference to FIG. 5 , where first storage system 402 calculates a set ofdeduplication hashes for first data 452 and compares the first set ofdeduplication hashes with a second set of deduplication hashes based onsecond data 456 stored on storage system 454. In this first technique,different quantities of matching hashes from the different sets ofdeduplication hashes for the different data stored on the differentstorage systems may indicate different levels of similarity between thedata, where a level of similarity is correlated to a quantity ofmatching hashes. Further, the level of similarity may serve as a basisfor determining whether or not migrating data would result in morebenefits than costs. In some examples, determining (404) a level ofsimilarity may be performed by a secondary controller within a multiplecontroller storage array within first storage system 402, where thesecondary controller is further described with reference to FIG. 1Aabove.

Another technique for determining (404) a level of similarity 458between first data 452 and second data 456 may be implemented by firststorage system 402 determining respective quantities of storage usagecorresponding to respective types of data and comparing the respectivequantities of storage usage and the corresponding respective types ofdata against respective quantities of storage usage corresponding torespective types of data stored on second storage system 454. In thisexample, each storage system may maintain a log that correlatesquantities of stored data with a type for the stored data, and anyparticular storage system may request such log information from otherstorage systems. In this way, storage system 402, or some given storagesystem or some given cloud-based management system receiving the loginformation, may determine, based on a total of data storage usage of adata type that matches, or is similar to, data types on another storagesystem, that using a particular one or more algorithms or techniques forreducing storage space use may result in lower storage space use on aparticular storage system. For example, if a data compression techniqueis particularly effective on image data, and if a large amount of storeddata on the different systems is image data, then applying the datacompression technique—after migrating the image data onto a singlestorage system— would reduce storage space usage as compared to notmigrating the image data and applying the data compression techniqueindependently on the respective image data on the separate storagesystems. In other examples, instead of, or in addition to, datacompression, other data reduction techniques may be applied, includingdata deduplication.

In another technique for determining (404) a level of similarity 458between first data 452 and second data 456 may be implemented by firststorage system 402 determining respective quantities of storage usagecorresponding to respective workload types that generate the data andcomparing the respective quantities of storage usage that correspond tothe respective workload types on first storage system 402 againstrespective quantities of storage usage that correspond to the respectiveworkload types on second storage system 454. For example, if a portionof the stored data on first storage system 402 was generated by aparticular database service workload type, and if another portion ofstored data on the second storage system 402 was also generated by asimilar database service, then this similarity of workload types mayserve as a basis for determining a level of similarity.

In another technique for determining (404) a level of similarity 458, anentity that is independent of any given storage system, such as acloud-based data storage management service, may query or receiveinformation that characterizes data stored on a given storage system,where the characterization data may serve as a basis for determininglevels of similarity of data among different storage systems. Forexample, the characterization data may include one or more of: sets ofdeduplication hashes, types and quantity of data, or quantities of datacorresponding to workload types.

The example method depicted in FIG. 4 also includes determining (406),in dependence upon the level of similarity 458, that an expected amountof storage space reduction from migrating similar data exceeds athreshold level 460 may be implemented by comparing a percentage valuerepresenting the level of similarity with a threshold level. Further,determining a threshold level may be implemented using differenttechniques. In one technique, where the level of similarity is based ona quantity of matching hash values between deduplication hash values offirst data 452, a threshold level may be specified as a matchingpercentage of hash values, where a matching percentage may be a defaultvalue or a value specified by a user or administrator.

With regard to determining a threshold level, if the level of similarityis small, then the resources used in migrating the data may outweighpotential benefits of the reduction in storage space usage. As oneexample, if, based on a level of similarity, an expected reduction isdata storage usage after migration is 3%, then the 3% expected reductionin storage space usage is compared to a threshold value determined to bea threshold above which benefits of a migration outweigh the resourcesused in migrating the data. In one example implementation, thisthreshold value may be 5%, however, the threshold value may be specifiedto be any value, and the threshold value may further be variable anddependent on current system workloads. For example, on an idle system,the threshold value may be correspondingly scaled lower, and on a busysystem, the threshold value may be correspondingly scaled higher.

Generally, for each of these techniques for determining a thresholdlevel, a matching percentage may be determined dynamically based on oneor more metrics such as network latencies, bandwidth restrictions, timeof day, current storage system workloads, or predicted storage systemworkload, where a matching percentage may be increased or decreased independence upon one or more of these or other metrics. For example, amatching percentage may initially be set to 10%, where if metricsindicate that storage system is lightly loaded, and is expected toremain lightly loaded for a window of time in which a migration mayoccur, then the matching percentage may be lowered to 5%. Generally, amatching percentage may be correlated to a resource impact of amigration, where the lower a resource impact of a migration isdetermined to be, then the lower the matching percentage is defined tobe, where a resource impact of a migration may be defined according toone or more of the aforementioned metrics.

The example method depicted in FIG. 4 also includes, responsive todetermining (406) that the expected amount of storage space reductionexceeds the threshold level, initiating (408) a migration of one or moreportions of the first data 452 from the first storage system 402 to thesecond storage system 454. Initiating (408) a migration of one or moreportions of the first data 452 from the first storage system 402 to thesecond storage system 454 may be implemented using different techniques.Further, the one or more portions of the first data may be all of thefirst data, a quantity sufficient to meet threshold level 460, or aquantity that corresponds to a unit of size resulting in a moreefficient data migration as compared to other units of size. In onetechnique, initiating (408) the migration may include generating anotification indicating one or more aspects of a proposed datamigration, and providing the notification to a user interface, such as adata management console, where a migration may be initiated in responseto an authorization received from a user approving the data migrationproposed via the management console. A notification may include one ormore of: an amount of data to be migrated, an expected reduction inoverall storage capacity, an expected amount of time or resourcesrequired for the data migration, levels of storage capacity subsequentto the proposed data migration, and the storage systems involved in theproposed data migration. In some cases, a user may authorize the entireproposed data migration, or the user may authorize a portion of theproposed data migration, where the quantity authorized is the quantitythat is migrated.

In another technique, initiating (408) the migration of the one or moreportions of the first data 452 from the first storage system 402 to thesecond storage system 454 may be implemented by automatically initiatinga data migration in response to determining (406) that the expectedamount of storage space reduction exceeds the threshold level 460.

In this way, a specific advantage for a given set of independent storagesystems, subsequent to a data migration of the one or more portions offirst data 452 among the set of independent storage systems, is that theoverall use of storage capacity among the set of independent storagesystems is less than prior to migration of the one or more portions offirst data 452. In different cases, a storage system may be consideredindependent from another storage system based on being implemented ondifferent storage area networks, being implemented at differentgeographic sites, or some other factor.

For further explanation, FIG. 5 sets forth a flow chart illustrating anexample method for storage efficiency driven migration according to someembodiments of the present disclosure.

The example method depicted in FIG. 5 is similar to the example methoddepicted in FIG. 4 , as the example method depicted in FIG. 5 alsoincludes: determining (404) a level of similarity between first data 452stored on a first storage system 402 and second data 456 stored on asecond storage system 454; determining (406), in dependence upon thelevel of similarity 458, that an expected amount of storage spacereduction from migrating similar data exceeds a threshold level 460; andresponsive to determining (406) that the expected amount of storagespace reduction exceeds the threshold level, initiating (408) amigration of one or more portions of the first data 452 from the firststorage system 402 to the second storage system 454.

However, the example method depicted in FIG. 5 further specifiesdetermining (404) the level of similarity between first data 452 storedon first storage system 402 and second data 456 stored on second storagesystem 454 to include: calculating (502) a first set of deduplicationhashes 552 based on first data 452 stored on first storage system 402;receiving (504) a second set of deduplication hashes 554 from secondstorage system 454; and comparing (506) first set of deduplicationhashes 552 to second set of deduplication hashes 554 to determine aquantity of matching hash values between hash values from first set ofdeduplication hashes 552 and hash values from second set ofdeduplication hashes 554, where the level of similarity is dependentupon the quantity of matching hash values.

Calculating (502) first set of deduplication hashes 552 may beimplemented by a management module implemented within storage system 402selecting a particular deduplication algorithm from among multiplepossible deduplication algorithms, and applying the deduplicationalgorithm some or all of the stored data within a storage system. Inthis example, the particular deduplication algorithm may be applied tofirst data 456 to calculate first set of deduplication hashes 554.Similarly, any storage system participating within the data storageefficiency data migration may calculate (502) a corresponding set ofdeduplication hashes. Further, any given storage system from among theparticipating storage systems may serve as a leader, where a leaderreceives, or requests, information from other storage systems todetermine a level of similarity, where in this example, the informationincludes sets of deduplication hashes. A leader may be designated as aleader for a period of time, through a voting procedure, or some othermethod, where loss of a leader may trigger a round of voting todetermine a new leader storage system.

Receiving (504) second set of deduplication hashes from second storagesystem 454 may be implemented by storage system 402 receiving, at acommunication port, a message from second storage system 454, where thecommunication port may implement a bus protocol, a network protocol, orsome other communication protocol. In another example, instead ofreceiving (504) second set of deduplication hashes, storage system 402may request a set of deduplication hashes on a periodic or aperiodicbasis, or in response to some triggering event.

Comparing (506) first set of deduplication hashes 552 to second set ofdeduplication hashes 554 to determine a quantity of matching hash valuesmay be implemented by storage system 402 iterating over the hash valuesof first set of deduplication hashes 552, and for each given hash value,searching for the given hash value within second set of deduplicationhashes, where for each match, a counter is incremented. Further, amatching percentage may be calculated to represent the number of matchesas compared to the total number of comparisons, where the matchingpercentage, as discussed above, may be used to indicate a level ofsimilarity.

For further explanation, FIG. 6 sets forth a flow chart illustrating anexample method for storage efficiency driven migration according to someembodiments of the present disclosure. The example method depicted inFIG. 6 is similar to the example method depicted in FIG. 4 , as theexample method depicted in FIG. 6 also includes: determining (404) alevel of similarity between first data 452 stored on a first storagesystem 402 and second data 456 stored on a second storage system 454;determining (406), in dependence upon the level of similarity 458, thatan expected amount of storage space reduction from migrating similardata exceeds a threshold level 460; and responsive to determining (406)that the expected amount of storage space reduction exceeds thethreshold level, initiating (408) a migration of one or more portions ofthe first data 452 from the first storage system 402 to the secondstorage system 454.

However, the example method depicted in FIG. 6 further specifiesdetermining (406) that an expected amount of storage space reductionfrom migrating similar data exceeds a threshold level to includedetermining (602) one or more storage space reduction results from anapplication of one or more functions for storage space reduction, wherethe one or more functions includes one or more of: data deduplication ordata compression.

Determining (602) one or more storage space reduction results from anapplication of one or more functions for storage space reduction may beimplemented using different techniques. In one technique for determining(602) the one or more storage space reduction results, where the one ormore functions include a data deduplication algorithm as depicted inFIG. 5 , storage system 402 may use the matching percentage calculatedfrom comparing (506) first set of deduplication hashes 552 to second setof deduplication hashes 554. In this example, the one or more storagespace reduction results may be based on the matching percentage and thecorresponding quantity of storage space represented by the matchinghashes. Using another technique for determining (602) the one or morestorage space reduction results, where the one or more functions includedata compression, the one or more storage space reduction results may bebased on expected data compression ratios for to a particular datacompression algorithm and a data type. For example, a table may store anexpected data compression ratio for a particular data compressionalgorithm applied to a particular data type, and based on a quantity ofdata of that particular data type, and the expected data compressionratio, an expected compressed size for the quantity of data may bedetermined. A similar calculation may be performed for each dataquantity, and respective data type, where the data quantity, andrespective data type, is specified to be a combined data quantity forthat data type from among both first data 452 and second data 456.

For further explanation, FIG. 7 sets forth a flow chart illustrating anexample method for storage efficiency driven migration according to someembodiments of the present disclosure. The example method depicted inFIG. 7 is similar to the example method depicted in FIG. 4 , as theexample method depicted in FIG. 7 also includes: determining (404) alevel of similarity between first data 452 stored on a first storagesystem 402 and second data 456 stored on a second storage system 454;determining (406), in dependence upon the level of similarity 458, thatan expected amount of storage space reduction from migrating similardata exceeds a threshold level 460; and responsive to determining (406)that the expected amount of storage space reduction exceeds thethreshold level, initiating (408) a migration of one or more portions ofthe first data 452 from the first storage system 402 to the secondstorage system 454.

However, the example method depicted in FIG. 6 further specifiesinitiating (408) the migration of the one or more portions of first data452 from first storage system 402 to second storage system 454 toinclude generating (702) a notification for authorization to migrate theone or more portions of first data 452 from first storage system 402 tosecond storage system 454, where initiating (408) the migration is inresponse to receiving an authorization from a user.

Generating (702) a notification for authorization to migrate the one ormore portions of first data 452 may be implemented by generating analert for a data management user interface, such as a managementconsole, where the alert includes information describing one or more of:expected data storage usage reductions expected from migrating the oneor more portions of first data 452 from first storage system 402 tosecond storage system 454, a size of the one or more portions of firstdata 452, one or more workloads associated with the one or more portionsof first data 452, expected time needed to perform the migration, orexpected computational resources to perform the migration. Given analert, a user may indicate, for example by selecting a user interfaceelement to approve the proposed migration described in an alert, thatthe migration is approved or rejected. In response to the userselection, storage system 402 may cancel the migration, or initiate the(408) the proposed migration.

For further explanation, FIG. 8 sets forth a flow chart illustrating anexample method for storage efficiency driven migration according to someembodiments of the present disclosure. The example method depicted inFIG. 8 is similar to the example method depicted in FIG. 4 , as theexample method depicted in FIG. 8 also includes: determining (404) alevel of similarity between first data 452 stored on a first storagesystem 402 and second data 456 stored on a second storage system 454;determining (406), in dependence upon the level of similarity 458, thatan expected amount of storage space reduction from migrating similardata exceeds a threshold level 460; and responsive to determining (406)that the expected amount of storage space reduction exceeds thethreshold level, initiating (408) a migration of one or more portions ofthe first data 452 from the first storage system 402 to the secondstorage system 454.

However, the example method in FIG. 8 further includes determining (802)a migration direction to be from first storage system 402 to secondstorage system 454 based on one or more of: relative workload levels atthe first storage system and the second storage system, relative storagecapacity availability at the first storage system and the second storagesystem, a user indication, or relative storage capacity improvementsdependent upon whether data is migrated from the first storage system tothe second storage system or data is migrated from the second storagesystem to the first storage system. Determining (802) a migrationdirection may be implemented by, for each basis, determining a betterdirection and a corresponding weighted value. For example, if a relativeworkload is lighter on first storage system 402 than on storage system454, then this may result in a weighted value in favor of moving in thedirection of first storage system 402. Similarly, if a relative storagecapacity is lower on storage system 402 than on storage system 454, thenthis may result in a weighted value in favor of moving in the directionof second storage system 454, where the weighted value may be furtheradjusted depending on the disparity in relative available storagecapacities. Such a calculation may be applied for each basis, where asummation of each calculation may indicate a direction in which tomigrate data. In some examples, a user may be provided with thesecalculations to generate a recommendation, and such a recommendation maybe overridden by a user indication.

For further explanation, FIG. 9 sets forth a flow chart illustrating anexample method for storage efficiency driven migration according to someembodiments of the present disclosure. The example method depicted inFIG. 9 is similar to the example method depicted in FIG. 4 , as theexample method depicted in FIG. 9 also includes: determining (404) alevel of similarity between first data 452 stored on a first storagesystem 402 and second data 456 stored on a second storage system 454;determining (406), in dependence upon the level of similarity 458, thatan expected amount of storage space reduction from migrating similardata exceeds a threshold level 460; and responsive to determining (406)that the expected amount of storage space reduction exceeds thethreshold level, initiating (408) a migration of one or more portions ofthe first data 452 from the first storage system 402 to the secondstorage system 454.

However, the example method depicted in FIG. 9 further specifiesinitiating (408) the migration of the one or more portions of first data452 from first storage system 402 to second storage system 454 toinclude determining (902) that the one or more portions of first data452 fit within second storage system 454, where initiating (408) themigration of the one or more portions of first data 452 is dependentupon determining (902) that the one or more portions of first data 452fit within second storage system 454.

Determining (902) that that the one or more portions of first data 452fit within second storage system 454 may be implemented by identifyingavailable storage resources, determining an amount of storage capacityon the storage resources, identifying one or more workload typesexecuting on second storage system 454, and determining an amount ofsystem resources consumed in order to determine whether or not the oneor more portions of first data 454 fit within second storage system 454.

Further, in some examples, determining whether or not data to bemigrated from a source storage system will fit within a target storagesystem may be based on the amount of storage occupied by the migrateddata after one or more data reduction techniques have been applied. Inthis case, data migrated may be data that is deduplicated, orcompressed, prior to being migrated, which has the added advantage ofusing fewer network resources than migrating the data as it is stored onthe source storage system.

Identifying available storage resources may include identifying one ormore types of system resources in a storage array. The one or more typesof system resources can include, for example, computing resources suchas CPUs, storage resources such as SSDs, memory resources such as RAM,write caching resources such as a write buffer device, and many others.Readers will appreciate that by identifying one or more types of systemresources in a storage array, the storage array may be viewed and evengraphically depicted as a multidimensional dimensional object, whereeach axis corresponds to a particular type of resource.

Determining an amount of storage capacity may include determining, forthe one or more types of system resources on a storage array, an amountof availability of the resource type.

Determining an amount of availability for the one or more types ofsystem resources on the storage array may be carried out by determiningthe amount of storage capacity that may be provided by the storageresources such as SSDs in the storage array, by determining the numberof IOPS that may be provided by the storage resources such as SSDs inthe storage array, by determining an amount of data per unit of timethat may be written to or read from by the storage resources such asSSDs in the storage array, and so on.

Identifying one or more workload types executing on second storagesystem 454 may include identifying one or more workload types executingon second storage system 454. The one or more workload types may bespecified in general terms such as, for example, a database application,a virtual desktop infrastructure, and many others. The workload types,to the extent that they are identifiable, may even be characterized at afiner level of granularity such as, for example, an Oracle™ database, anIBM™ DB2 database, and so on. Identifying one or more workload typesexecuting on a storage system may be carried out, for example, bydetermining an I/O pattern for the storage array and comparing the I/Opattern to I/O patterns exhibited by known workload types, by examiningdata stored on the storage array to identify metadata that is indicativeof a particular workload type, by identifying characteristics (e.g.,block size) of data to identify data characteristics that are indicativeof a particular workload type, and so on.

Determining an amount of system resources consumed may includedetermining, for each of the one or more workload supported by thestorage system, an amount of system resources consumed by each instanceof the workload type. Determining an amount of system resources consumedby each instance of a particular workload type may be carried out, forexample, by dividing the total amount of resources consumed by allinstances of a particular workload type by the number of instances ofthe workload type. Consider an example where the workload type is avirtual machine. In such an example, determining an amount of systemresources consumed by each instance of a virtual machine may be carriedout, for example, by dividing the total amount of resources consumed byall virtual machines by the number of virtual machines supported by thestorage array.

In this way, using this information, storage system 402 may determinewhether or not the one or more portions of first data 454 fit withinsecond storage system 454 according to available resources, workloadtypes, and amounts of storage resources expected to be consumed.

For further explanation, FIG. 10 sets forth a flow chart illustrating anexample method for storage efficiency driven migration according to someembodiments of the present disclosure. Although depicted in less detail,the data management service 1002 depicted in FIG. 10 may be similar tothe storage systems described above with reference to FIGS. 1A-1D, FIGS.2A-2G, FIGS. 3A-3C, or any combination thereof. Further, the storagesystem depicted in FIG. 10 may include the same, fewer, or additionalcomponents as the storage systems described above.

In this example, data management service 1002 may be implemented withina cloud services provider, such as cloud services provider 302 depictedin FIG. 3A, in communication with multiple different storagesystems—similar to the communication network depicted between cloudservice provider 302 and storage system 306 depicted in FIG. 3A. Inother examples, data management service 1002 may be implemented withinone of the multiple storage systems implementing storage efficiencydriven migration.

The example method depicted in FIG. 10 includes receiving (1004), fromfirst storage system 1052, first set of deduplication hashes 1056 basedon data 1054 stored on second storage system 1052. Receiving (1004)first set of deduplication hashes 1056 may be implemented by datamanagement service 1002 receiving, at a communication port, a messagefrom first storage system 1052, where the communication port mayimplement a bus protocol, a network protocol, or some othercommunication protocol. In another example, instead of receiving (1004)first set of deduplication hashes, data management service 1002 mayrequest a set of deduplication hashes on a periodic or aperiodic basis,or in response to some triggering event.

The example method depicted in FIG. 10 also includes receiving (1006),from second storage system 1062, second set of deduplication hashes 1066based on data 1064 stored on second storage system 1062. Receiving(1006) second set of deduplication hashes 1066 may be implementedsimilar to receiving (1004) first set of deduplication hashes 1056.

The example method depicted in FIG. 10 also includes initiating (1008),in dependence upon a comparison of one or more hash values from firstset of deduplication hashes 1056 to one or more hash values from secondset of deduplication hashes 1066, a migration of data from first storagesystem 1052 to second storage system 1062. Initiating (1008) themigration of data from first storage system 1052 to second storagesystem 1062 may be implemented similar to the techniques described abovewith reference to FIG. 4 and initiating (408) a migration of one or moreportions of first data 452 from first storage system 402 to secondstorage system 454.

Example embodiments are described largely in the context of a fullyfunctional computer system implementing a storage system. Readers ofskill in the art will recognize, however, that the present disclosurealso may be embodied in a computer program product disposed uponcomputer readable storage media for use with any suitable dataprocessing system. Such computer readable storage media may be anystorage medium for machine-readable information, including magneticmedia, optical media, or other suitable media. Examples of such mediainclude magnetic disks in hard drives or diskettes, compact disks foroptical drives, magnetic tape, and others as will occur to those ofskill in the art. Persons skilled in the art will immediately recognizethat any computer system having suitable programming means will becapable of executing the steps of the method as embodied in a computerprogram product. Persons skilled in the art will recognize also that,although some of the example embodiments described in this specificationare oriented to software installed and executing on computer hardware,nevertheless, alternative embodiments implemented as firmware or ashardware are well within the scope of the present disclosure.

Embodiments can include a system, a method, and/or a computer programproduct. The computer program product may include a computer readablestorage medium (or media) having computer readable program instructionsstored thereon for causing a processor to carry out aspects of thepresent disclosure.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present disclosure may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present disclosure.

Aspects of the present disclosure are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to some embodimentsof the disclosure. It will be understood that each block of theflowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, can beimplemented by computer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present disclosure. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

Readers will appreciate that the steps described herein may be carriedout in a variety of ways and that no particular ordering is required. Itwill be further understood from the foregoing description thatmodifications and changes may be made in various embodiments of thepresent disclosure without departing from its true spirit. Thedescriptions in this specification are for purposes of illustration onlyand are not to be construed in a limiting sense. The scope of thepresent disclosure is limited only by the language of the followingclaims.

What is claimed is:
 1. A method comprising: determining a level ofsimilarity between first data stored on a first storage system andsecond data stored on a second storage system; determining, independence upon the level of similarity, that an expected amount ofstorage space reduction from migrating similar data exceeds a thresholdlevel; and responsive to determining that the expected amount of storagespace reduction exceeds the threshold level, initiating a migrationincluding selecting, based on storage efficiency parametersautomatically without user input, a migration direction from one ofeither migrating the first data from the first storage system to thesecond storage system and migrating the second data from the secondstorage system to the first storage system.
 2. The method of claim 1,wherein determining the level of similarity between the first datastored on the first storage system and the second data stored on thesecond storage system comprises: comparing a first set of deduplicationhashes based on the first data stored on the first storage system to asecond set of deduplication hashes received from a second storage systemto determine a quantity of matching hash values between hash values fromthe first set of deduplication hashes and hash values from the secondset of deduplication hashes, wherein the second set of deduplicationhashes is based on the second data stored on the second storage system;wherein the level of similarity is dependent upon the quantity ofmatching hash values.
 3. The method of claim 2, wherein the first datainclude one or more of the matching hash values.
 4. The method of claim1, wherein the level of similarity is dependent upon a quantity of dataof similar types stored within the first storage system and the secondstorage system.
 5. The method of claim 1, wherein determining that theexpected amount of storage space reduction from migrating similar dataexceeds the threshold value comprises: determining one or more storagespace reduction results from an application of one or more functions forstorage space reduction, wherein the one or more functions include oneor more of: data deduplication or data compression.
 6. The method ofclaim 1, wherein the first storage system comprises a primary controllerand a secondary controller, and wherein the migration is performed bythe secondary controller of the first storage system.
 7. The method ofclaim 1, wherein initiating the migration comprises: generating anotification for authorization to migrate the first data from the firststorage system to the second storage system; and wherein initiating themigration is in response to receiving the authorization from a user. 8.The method of claim 1, wherein the storage efficiency parameters includeat least one of: relative workload levels at the first storage systemand the second storage system, relative storage capacity availability atthe first storage system and the second storage system, or relativestorage capacity improvements dependent upon whether data is migratedfrom the first storage system to the second storage system or data ismigrated from the second storage system to the first storage system. 9.The method of claim 1, wherein initiating the migration comprises:determining that the first data fits within the second storage system;and wherein initiating the migration is dependent upon determining thatthe first data fits within the second storage system.
 10. An apparatuscomprising a computer processor, a computer memory operatively coupledto the computer processor, the computer memory having disposed within itcomputer program instructions that, when executed by the computerprocessor, cause the apparatus to carry out the steps of: determining alevel of similarity between first data stored on a first storage systemand second data stored on a second storage system; determining, independence upon the level of similarity, that an expected amount ofstorage space reduction from migrating similar data exceeds a thresholdlevel; and responsive to determining that the expected amount of storagespace reduction exceeds the threshold level, initiating a migrationincluding selecting, based on storage efficiency parametersautomatically without user input, a migration direction from one ofeither migrating the first data from the first storage system to thesecond storage system and migrating the second data from the secondstorage system to the first storage system.
 11. The apparatus of claim10, wherein determining the level of similarity between first datastored on the first storage system and the second data stored on thesecond storage system comprises: comparing a first set of deduplicationhashes based on the first data stored on the first storage system to asecond set of deduplication hashes received from a second storage systemto determine a quantity of matching hash values between hash values fromthe first set of deduplication hashes and hash values from the secondset of deduplication hashes, wherein the second set of deduplicationhashes is based on the second data stored on the second storage system;wherein the level of similarity is dependent upon the quantity ofmatching hash values.
 12. The apparatus of claim 11, wherein the firstdata includes one or more of the matching hash values.
 13. The apparatusof claim 10, wherein the level of similarity is dependent upon aquantity of data of similar types stored within the first storage systemand the second storage system.
 14. The apparatus of claim 10, whereindetermining that the expected amount of storage space reduction frommigrating similar data exceeds the threshold value comprises:determining one or more storage space reduction results from anapplication of one or more functions for storage space reduction,wherein the one or more functions include one or more of: datadeduplication or data compression.
 15. The apparatus of claim 10,wherein the first storage system comprises a primary controller and asecondary controller, and wherein the migration is performed by thesecondary controller of the first storage system.
 16. The apparatus ofclaim 10, wherein initiating the migration comprises: generating anotification for authorization to migrate the first data from the firststorage system to the second storage system; and wherein initiating themigration is in response to receiving the authorization from a user. 17.The apparatus of claim 10, wherein the storage efficiency parametersinclude at least one of: relative workload levels at the first storagesystem and the second storage system, relative storage capacityavailability at the first storage system and the second storage system,or relative storage capacity improvements dependent upon whether data ismigrated from the first storage system to the second storage system ordata is migrated from the second storage system to the first storagesystem.
 18. The apparatus of claim 10, wherein initiating the migrationcomprises: determining that the first data fits within the secondstorage system; and wherein initiating the migration is dependent upondetermining that the first data fits within the second storage system.